This open learning pack is designed to help you study and work towards your dissertation and fulfil the learning

objectives for the module.

The dissertation is a piece of research that shows you have the capability to carry out the research process in an

independent and thorough way. It brings together all the research skills that you have developed over the past two or

three years while studying other modules on the degree and enables you to study a topic of your choice in more

depth. We take you through all the stages of the process and give guidance on how to write a research proposal and

the final dissertation. It is designed for you to work through on your own and gives lots of activities for you to

complete. In addition, it is important that you undertake additional investigation into research methods as we can only

give you the basic guidelines here. For example, once you have decided on a particular method to use you will need

to read up on that method in a number of research methods textbooks. Your tutor or supervisor can help you with any

aspects that you find difficult.

The first thing to establish is the nature of the research process. We cover this now.

 

There is no agreement or consensus between writers on how the word should be defined or interpreted. One reason

for this is that ‘research’ means different things to different people, for example:

Children at school research their local environment.

1. People research the times of trains from Waterloo to Paris.

2. Scientists research the effects of genetically modified food.

3. PhD students research and extend knowledge in their subject area.

A useful starting point in answering the question is to see how research is defined in a dictionary.

Activity I.1

Look up the definition of the word research in a number of dictionaries, such as Collins, Oxford English Dictionary,

Chambers, Websters, Collins Dictionary of Sociology etc.

Dictionary definitions use words such as ‘systematic’, ‘careful’, ‘facts’, ‘information’, and ‘investigation’. However, the

problem with these definitions is they are not sufficiently rigorous or detailed for our purposes. For example, the word

‘information’ is often used when ‘data’ should be used.

From the many definitions offered in research methods textbooks, there is some agreement that research:

is a process of gathering facts (data)

is systematic

reviews, questions and synthesises existing knowledge

involves analysis

possibly increases knowledge

is a combination of all of these

Research is about process (the approach you take) and thinking (questioning, synthesis, analysis, criticality). As

you work through this material, we discuss process and the intellectual activity – thinking.

 

Three words that occur very regularly in research texts are concept, theory and model. It is often assumed that

everyone knows what these words mean and what the differences between them are. These are usually false

premises. The terms will be defined and briefly discussed. As in most situations there are a number of possible

definitions for each word.

Concept

Simply, a concept is an abstract notion or idea, something that isn’t concrete.

"A word or set of words that expresses a general idea concerning the nature of something or the relations between

things, often providing a category for the classification of phenomena."

Theodorson & Theodorson 1969

In other words a concept is an abstract summary of characteristics that we see as having something in common.

Concepts are created by people for the purpose of communication and efficiency.

A concept has no set meaning and it is up to us to define what we mean by the concept. But if concepts have no set

meaning then anyone can define a concept in any way that they wish. But if everyone can define the concept in any

way they like the concept becomes worthless; unless there is agreement on the meaning communication is

impossible. A concept therefore has to be defined, but in such a way that it has a degree of acceptance. Experts in

the field usually propose such definitions.

As a researcher you would be expected to:

review this range of definitions, and

decide on which you are going to use.

Theory

A very loose meaning of the word is:

That part of the study of a subject which is not practical.

For example, teaching theory is often contrasted with teaching practice.

More substantial definitions of a theory are:

"A theory is a set of interrelated principles and definitions that present a systematic view of phenomena by specifying

relationships among variables with the purpose of explaining natural phenomena."

Kerlinger 1986

"Any set of hypotheses or principles linked by logical or mathematical arguments which is advanced to explain an

area of empirical reality of type of phenomenon."

Jary & Jary 1995

In effect a theory includes a set of basic assumptions and axioms as the foundation and the body of the theory is

composed of logically interrelated, empirically verifiable propositions.

Let us look at one of these theories in more detail.

Motivation theories fall into two main groups – content theories and process theories. Content theories of motivation,

such as Maslow’s hierarchy of needs and Herzberg’s two factor theory of motivation, focus on what motivates people.

Process theories, such as Expectancy theory and Equity theory, place more emphasis on how people become

motivated. If we look at one of these theories, Maslow is based on a set of assumptions and links a number of

variables (physiological, security social, self-esteem and self-satisfaction) to explain motivation. (Torrington and Hall,

1995)

Concepts are generally regarded as being at a lower level of abstraction than a theory but a necessary part of any

theory, since theories are formed from concepts.

Model

Lucey (1991) defines a model of "any simplified abstract of reality ".

For example we are all familiar with scale models of aircraft, cars, ships, housing estates, etc. These simplified

versions of the real thing are called physical or iconic models. They are based directly on the representation of the

phenomenon being studied and look like the object.

An extension of the physical model is the analogue model. These models are physical in form but do not have the

same appearance as the object being investigated. The circular movement of the hands of a wristwatch is an

analogue of the behaviour of time.

However there are other types of models.

Symbolic models are based on logic, and inter-relationships between concepts are usually expressed

mathematically or algebraically. They are concerned with quantification.

Mathematical (algebraic) equations are symbolic models. For instance a simple mathematical model is:

Profit = Revenue minus Total Cost

or P = R – TC

There are many such symbolic models in the fields of economics, finance, statistics, science and engineering. One

approach to the analysis of such models is to represent the model on a spreadsheet and conduct sensitivity analysis.

A conceptual model is composed of a pattern of interrelated concepts but not expressed in mathematical form and

primarily not concerned with quantification. Diagrams, such as maps, graphs, charts, balance sheets, circuit

diagrams, and flowcharts, are often used to represent such models.

Models may be very simple or very complex. Since the world we observe cannot be observed in totality, each model

reflects only a limited aspect of the total world. No single model, or combination of models, reveals the truth of the

structure of reality. Each model reveals and orders reality from a particular perspective.

In practice concepts and especially theories are often referred to as models.

Other words associated with concepts theories and models are law, empirical and variable.

A law is a precise statement of a relationship among facts that has been repeatedly corroborated by scientific

investigation and is generally accepted as accurate by experts in the field. Laws are generally derived from a theory.

A law is frequently referred to as a universal and predictive statement. It is universal in the sense that the stated

relationship is held always to occur under the specified conditions, although the conditions may be predicted to follow.

Empirical means based on experience, observation or experimentation. Empiricism is the belief that all human

knowledge is derived from experience – as opposed to, for example, idealism, rationalism and naturalism.

A variable is a characteristic or attitude that changes or varies. More exactly, it is any measurable characteristic

which can assume varying or different values in successive individuals cases.

In the mathematical sense it is a quantity that may take any one of a specified set of values, for example, height.

A wider use of the term variable includes mathematically non-measurable characteristics such as gender and religion.

It is usual, when comparisons are made between two variables or there is a relationship between two variables, to

term one the dependent variable and the other the independent variable. The independent variable is the variable

that is changed or manipulated. As a consequence of this change there will be a resulting change in the other

variable – dependent variable. For example, research may be conducted into the intensity of lighting in a room in

order to observe the effect on productivity levels of workers. The independent variable is the intensity of lighting and

the dependent variable is the level of production.

 

The research process or methodology is the approach to the entire study – it is the

master plan. It is the blueprint for achieving your objectives, one of which is the

production of the dissertation. Irrespective of the research you are going to

conduct, there are several fundamental stages you will have to go through. The

diagram below is a simplified, traditional and highly structured view of the

research process.

The diagram shows the systematic nature of the research process. Unfortunately it is not quite so

straightforward as many of the stages overlap and there is much ‘looping back’ to previous stages.

This simplified diagram does not show the underpinning theoretical issues and questions that have

to be addressed. The following diagram shows the different aspects to be considered under each

section.

As you can see each stage in the process has many aspects and issues to be considered. We cover

all of these stages in the units in this pack.

 

This unit is designed to help you get started in the research process and reach the stage of writing your research

proposal. We begin by looking at the theory of research and the different types of research, the actual research

process, and its outcome. We go through some decision-making stages to help you with your research proposal.

 

Superficially the research process can appear to be relatively simple - if you carry out the basic steps methodically

and carefully, then you should arrive at useful conclusions. However, the nature of research can be very complex and

when you are reading textbooks on research methodology you will come across many unfamiliar words and terms.

We first look at types of research and explain some of the terms.

Types of research

The main different types of research can be classified by its purpose, its process and its outcome. These can in turn

be broken down further:

The purpose of the research can be classified as:

o exploratory

o descriptive

o analytical

o predictive.

The process of the research can be classified as:

o quantitative

o qualitative.

The outcome of the research can be classified as:

o applied

o basic or pure

o action.

Let us look at these in more detail.

Purpose of research

Exploratory research

This is conducted when there are few or no earlier studies to which references can be made for information.

The aim is to look for patterns, ideas or hypotheses rather than testing or confirming a hypothesis. In

exploratory research the focus is on gaining insights and familiarity with the subject area for more rigorous

investigation later. In an undergraduate dissertation it is likely that you will be drawing on previous studies

and so pure exploratory research is not generally appropriate for studies at this level – it is more appropriate

for postgraduate research. However, it is possible that you may carry out an initial survey to establish areas

of concern (exploratory research) and then research these issues in more depth, perhaps through

interviews, to provide a deeper understanding (explanatory research).

Descriptive research

This describes phenomena as they exist. It is used to identify and obtain information on the characteristics of a

particular issue. It may answer such questions as:

o What is the absentee rate amongst a particular group of workers?

o What are the feelings of workers faced with redundancy?

The data collected are often quantitative, and statistical techniques are usually used to summarise the information.

Descriptive research goes further than exploratory research in examining a problem since it is undertaken to

ascertain and describe the characteristics of the issue. An undergraduate dissertation may include descriptive

research, but it is likely that it will also include one of the following two types (explanatory or predictive) as you are

required in your dissertation to go beyond description and to explain or predict.

Analytical or explanatory research

This is a continuation of descriptive research. The researcher goes beyond merely describing the

characteristics, to analyse and explain why or how something is happening. Thus, analytical research aims

to understand phenomena by discovering and measuring causal relations among them. It may answer

questions such as:

o How can the number of complaints made by customers be reduced?

o How can the absentee rate among employees be reduced?

o Why is the introduction of empowerment seen as a threat by departmental managers?

Predictive research

Predictive research goes further by forecasting the likelihood of a similar situation occurring elsewhere. It aims to

generalise from the analysis by predicting certain phenomena on the basis of hypothesised, general relationships. It

may attempt to answer questions such as:

o Will the introduction of an employee bonus scheme lead to higher levels of productivity?

o What type of packaging will improve our products?

Predictive research provides ‘how’, ‘why’, and ‘where’ answers to current events as well as to similar events in the

future. It is also helpful in situations where ‘What if?’ questions are being asked.

Process of research

There is no consensus about how to conceptualise the actual undertaking of research. There are, however, two main

traditions of approaching a research topic – quantitative and qualitative. Each approach demands different

research methods.

Quantitative research

The quantitative approach usually starts with a theory or a general statement proposing a general

relationship between variables. With this approach it is likely that the researchers will take an objective

position and their approach will be to treat phenomena as hard and real. They will favour methods such as

surveys and experiments, and will attempt to test hypotheses or statements with a view to generalising from

the particular. This approach typically concentrates on measuring or counting and involves collecting and

analysing numerical data and applying statistical tests.

Qualitative research

The alternative tradition is the qualitative approach. Here the investigator views the phenomena to be

investigated as more personal and softer. He or she will use methods such as personal accounts,

unstructured interviews and participant observation to gain an understanding of the underlying reasons and

motivations for peoples’ attitudes, preferences or behaviours. With this approach, the emphasis is more on

generating hypotheses from the data collection rather than testing a hypothesis.

In reading around the subject you will find many alternative names for qualitative and quantitative research.

It is good to have an understanding of these and to recognise them when you see them in research methods

textbooks.

The features and differences between the two research processes are detailed below.

You should note the following points:

Qualitative and quantitative research methods are not clear-cut nor mutually exclusive – most research

draws on both methods.

Both approaches can generate quantitative and qualitative data.

The difference between the two methods is in the overall form and in the emphasis and objectives of the

study.

Outcome of research

Applied research

Applied research is problem-oriented as the research is carried out to solve a specific problem that requires a

decision, for example, the improvement of safety in the workplace, or market research. For your dissertation it is not

usually acceptable to carry out applied research as it is very much limited to one establishment or company and you

are required to look at issues of wider significance, perhaps to your industry as a whole or to a sector of it. You may

have already carried out a problem-based piece of research related to your placement. It is important to understand

that the dissertation requires you to carry out some form of basic research – see below.

Basic research

Basic research is also called fundamental or pure research, and is conducted primarily to improve our

understanding of general issues, without any emphasis on its immediate application. It is regarded as the

most academic form of research since the principal aim is to make a contribution to knowledge, usually for

the general good, rather than to solve a specific problem for one organisation. This may take the form of the

following:

o Discovery – where a totally new idea or explanation emerges from empirical research which may

revolutionise thinking on that particular topic. An example of this would be the Hawthorne

experiments. (Gillespie, 1991)

o Invention – where a new technique or method is created. An example of this would be the

invention of TQM (total quality management).

o Reflection – where an existing theory, technique or group of ideas is re-examined possibly in a

different organisational or social context. For example, to what extent can Herzberg’s theory of

motivation be applied to front-line workers in the contract catering sector?

(Torrington & Hall, 1995)

For an undergraduate dissertation it is most likely that you will be concentrating on reflection, as the scope of the

project is unlikely to be large enough to consider discovery or invention.

Action research

This is a form of research where action is both an outcome and a part of the research. The researcher

‘interferes’ with or changes – deliberately – what is being researched. The critics of action research argue

that since the researcher is changing what is being researched during the process of research, the work

cannot be replicated. If it cannot be replicated its findings cannot be tested in other situations. This prevents

general knowledge being developed and thus it cannot contribute to theory. Also, as the researcher is

involved in the change process there is a loss of critical, detached objectivity. There are two approaches to

action research:

o Classical action research begins with the idea that if you want to understand something you

should try changing it.

o New paradigm research is based on a new model or framework for research. It claims that

research can never be neutral and that even the most static and conventional research exposes

the need for change in what is being researched. It involves inquiry into persons and relations

between persons, and is based on a close relationship between researcher and those being

researched. The research is a mutual activity of a ‘co-ownership’ involving shared power with

respect to the process and the outcomes of the research. Those being researched can, for

example, decide how the research will be undertaken, in what form and with what questions being

asked. The researcher is a member of a ‘community’ and brings to it special skills and expertise.

The researcher does not dictate what will happen. This type of research is most easily carried out

when working with individuals or small groups. It means that the researcher must be highly skilled

not only in research methods but also in the interpersonal skills of facilitating others. It is not,

therefore, usually appropriate for an undergraduate student who is carrying out a major piece of

research for the first time. Action research is often used by educationalists who are trying to

improve their own practice by making changes to the delivery of their classes and by observing and

asking students which actions work best.

As you can see, there are a number of types of research and not all may be suitable for you in your

dissertation. The key points to remember are as follows:

While the purpose of your dissertation may have some elements of exploratory or descriptive research you

should concentrate on research that will mainly fall into the explanatory area, or perhaps predictive research

if you are very confident. Explanatory research gives you the opportunity to demonstrate the skills of

analysis and evaluation which will help you to score highly in your final marks.

The process of your research can either be quantitative or qualitative and the different methods that can

help you to carry out your research in this way are outlined more fully in Unit 3.

It is likely that you will be carrying out basic or pure research in the reflection mode (rather than applied or

action research) as this will give you the best chance of showing that you can test out a theory in a new

situation.

Other research terms

You may find a number of research terms when reading about methodology and it will help if you have some

understanding of them as they can be confusing! The next activity will help you explore some of these terms.

Please do not worry too much if these terms seem confusing at this stage. It will gradually fall into place as you carry

on with this pack and do more reading around the subject. However, we hope this has demonstrated to you that there

is a lot involved in this research process!

 

A difference between a dissertation and almost any other piece of work is that you have to decide on a topic and the

title. You start with a blank sheet. This, for most students, is daunting, troublesome and challenging. So where do you

begin?

You begin with the ‘research proposal’. This is the document which sets out your initial ideas and thinking and shows,

to a certain extent, how much thinking you have devoted to the issue. The research proposal form specifies the need

for:

topic and title

a research question or hypothesis (not both)

a review of some literature associated with the title

some indication of how you are going to collect the primary data

a time plan

a bibliography of the literature consulted in putting the proposal together.

The key point about any research is that it has to concern something that you are interested in. Motivation in

undertaking research rises and falls. If you have no or little interest to start with, then it will be difficult to lift that

interest should you encounter problems and a drop in motivation later on. In the following sections, we consider each

aspect of the proposal in more detail.

Topic and title

Where does the inspiration for your dissertation topic come from? There are various sources but the most common,

from which this interest may arise, are:

personal experience

something someone has said

something you have read

something you have studied

something you have not studied

your career aspirations.

What is an acceptable topic? Basically any topic is acceptable but:

it must be in the area of your major pathway

it has to be suitable for the level of study

there has to be a literature base which discusses the various theories (concept and model are alternative

words for theory) that underpin your topic.

Start by identifying the general topic area; then have a conversation with yourself that narrows the topic down – to

something that is more focussed – and then come up with main aim or purpose of the dissertation.

If you have more than one topic in mind

Perhaps you have more than one area in mind – if so, you should go through the above process with all of them to

help you decide.

Refining the aim – getting the title

Having stated your aim in one sentence, you now need to think about it in more detail to refine your ideas and

thinking. Hopefully at the end of this you will have a short, succinct title. To do this you need to have a conversation

with yourself. For the example on motivation this conversation may run as follows:

1. Here is how I see the issue. ‘Increased or enhanced motivation leads to increased productivity.’

But what are you referring to when you say ‘increased or enhanced motivation’? What actually happens in

the workplace when motivation is increased? Or put it another way, what causes motivation to be

enhanced? Possible answers are changes in the job design, management or leadership style, organisational

structure or reward system. Why not change your statement?

2. Right! ‘Changes (improvements) in job design, leadership style, organisational structure, reward systems

and so on, cause increased productivity.’

Well, this statement appears to be true, but surely it only happens when the individuals in question have the

ability to carry out the prescribed tasks in ways that are expected. Why not qualify it?

3. OK. ‘Changes (improvements) in job design, leadership style, organisational structure, reward systems and

so on, cause increased productivity when the individuals have the relevant ability (competencies).’

That is better, but by now you should be aware of some of the managerial implications of your chosen line of

research. You can see various new lines of research beginning to open even before you have completed the

design of your research. So, you have now got the flexibility to direct your enquiry along the lines you find

most interesting and appealing.

Why not go back to the original point of focus? Motivation and motivational factors are about individuals and

the outcome of motivation is satisfaction. Since your research idea is on workplace satisfaction your

concerns are with job satisfaction. Why not give this interpretation of the issue?

4. Right. ‘Changes (improvements) in job design, leadership style, organisational structure, reward systems

and so on lead to job satisfaction which causes increased productivity when the individuals have the

relevant ability (competencies).’

That looks even better, but couldn’t you shorten the statement?

5. ‘Job satisfaction causes increased productivity.’

That is short and sweet. What about your conclusion?

6. ‘Increased job satisfaction causes increased productivity, given the right conditions.’

Done!

A nice short title!

Notice the title does not begin with:

‘An investigation into …’

or

‘An analysis of …’

The very fact you are undertaking research implies you are investigating or analysing. Also the title is short – aim for

a maximum of 12 words in your title.

As you can see from this activity, a diverse range of factors determines job satisfaction. There are many examples of

this in the workplace. One example, relating to organisational factors, might be the effects on job satisfaction of a

major hotel rebuilding programme. A feeling of lack of involvement or knowledge of what is happening may lead to a

lot of resentment; moreover, building workers and noise can have a very disruptive effect on the daily work of a busy

hotel.

A dissertation would not cover all of these possibilities. It would probably concentrate on one or two at the most. The

above list shows there are at least 10 potential dissertations in this area. It is important that you narrow down your

topic to a very specific aspect for investigation. You are looking for depth not breadth.

Research questions

Whereas the aim or purpose statement explains the general direction of the study and is summarised by your title,

the research questions (or hypotheses) expand on this by providing detail. This is a critical stage in your research,

even though it appears early in the process.

If you do not ask the appropriate questions you will not be able to collect suitable data and arrive at sensible

conclusions. By research questions we do not mean the detailed questions you might use in interviews or

questionnaires, but questions which identify the general nature of research or issue you wish to focus on.

At the proposal stage we want the core or key question, or, to put it another way, we want a ‘grand tour’ question.

After further reading you might identify another key question, but remember, the more core questions that you have,

the more work you will need to do.

A core research question should imply:

an explanation of some phenomenon

a relationship between variables

a comparison between variables

prediction

analysis.

The types of questions that produce explanations and relationships may begin with:

This list is only for illustrative purposes and is not exhaustive. There are many other possibilities. A point to note, and

one that is often ignored by students, is that a question ends in a question mark.

Another example is:

In the above example, the researcher does not know if there is a difference between younger and older students and

is interested in determining this. However, suppose the researcher knows there is a difference (from other research)

and wants to find out why there is a difference. The aim of the dissertation and main research question will change,

even though the title remains the same.

Hypotheses

An alternative way of posing a research question is to state a hypothesis (plural hypotheses). A hypothesis is a

proposition about the area that you are studying and is expressed as a statement of fact or what you believe to be

true. You then try to find out whether the statement is true or false.

A ‘good’ hypothesis is:

based on current knowledge and understanding (facts, theory)

compares two variables

can be tested by the collection and analysis of data.

A hypothesis is worded such that it implies that the two variables are independent of each other. Strictly this is called

the null hypothesis. If we consider the example on the type of degrees obtained by younger and older students, we

can state the (null) hypothesis as:

There is no difference in the level of degree obtained by younger and older students.

or

Younger and older students do not differ in the level of degree attained.

This hypothesis is then tested by trying to disprove it by saying, ‘let us look for evidence that would show the

hypothesis to be incorrect’. In this example this means trying to show that there is a difference in the level of degree

obtained. If we could find sufficient evidence to show a difference we would reject the null hypothesis:

There is no difference in the level of degree obtained by younger and older students

in favour of the alternative hypothesis:

There is a difference in the level of degree obtained by younger and older students.

Of course, if you show there is a difference it introduces the questions, ‘What is the difference and why?’

The notion of a hypothesis is a difficult one and may not be necessary for your research. However, it is a good

exercise to try to phrase your research in this way as it helps to clarify your ideas.

Another type of hypothesis is a statistical hypothesis. These hypotheses tend to be used when researchers are

dealing with large amounts of numerical data. Also theoretical statistical tests are used to prove or disprove the null

hypothesis. Such hypotheses are unlikely to concern you as you will be handling smaller amounts of data.

Preliminary literature review

For the research proposal, you are required to write an essay that identifies the main underpinning

concepts/theories/models that are relevant to your topic/title/research question. This essay – the preliminary

literature review – is a much smaller version of the actual literature review that would be found in your dissertation,

but provides a starting point that you can use for development.

Primary data collection

As with the literature review you are being asked in the proposal to do something that you have not yet covered in

great detail. In particular, you have to try to identify how you are going to collect your primary data.

Time planning

You have now thought and written about the:

title

core research question or hypothesis

preliminary literature review and bibliography

primary data collection

The penultimate stage of the proposal is to produce a time plan of what you are going to do and when. The plan

should be detailed and include all the tasks necessary to complete your dissertation. Remember these are not

discrete – many of the tasks have to be thought about in advance and overlap with other activities. They also take a

lot longer than you actually think. For example, it is no good thinking that the literature review will take four weeks.

You have to spend time finding material, reading the material, writing a draft, submitting it to your supervisor, giving

him or her time to read it, get feedback, and redraft based on the comments.

Students often underestimate how long data analysis and evaluation takes. At undergraduate level it should take a

minimum of four weeks. Many students, because of poor planning, or things going, wrong find themselves short of

time towards the end of the dissertation and rush the analysis and evaluation. This often negates all the good work

that may have gone before.

A number of approaches are possible in preparing a time plan. The basic method is to list the weeks from the

commencement of the dissertation to the submission and slot in the detail. In this way you can identify holidays and

other times when you may not be able to work on the dissertation. You can also identify milestones and key dates.

Assessment of the proposal

By now you have almost completed the proposal. The final step is to reflect on your proposal. You probably are very

tempted to put in the final full stop and not look at it again! However, you need to reflect and re-assess what you have

written.

Remember that you have to convince the supervisors who assess your proposal that you know what you are talking

about, that you have given sufficient thought to the proposal and that you have devoted some effort to it. To do this,

you need to ask the same questions the supervisors ask when assessing your proposal:

Is the title clear and concise?

Is the core research question appropriate and answerable?

Does the preliminary literature review draw on authors from both textbooks and journals?

o Is it up-to-date?

o Is it sufficiently detailed?

o Is it descriptive or does it include discussion and debate?

o Is it written in a fluent, easy-to-read style?

Is the proposed primary data collection reasonable at this stage?

Is the time plan detailed and feasible?

Is the bibliography correct?

Has the proposal been spell-checked? Is it grammatically correct?

Does it look professional?

Hand in the proposal. Well done!

The literature review is a key part of your dissertation and it is your chance to show that you

have the skills of academic writing appropriate for an honours graduate. You should have used

all these skills before in your earlier studies but the dissertation takes the skills of reading and

writing to a higher level than you have achieved before. In this unit, we help you develop your

academic skills to the level required. These skills are: searching the literature; record keeping;

reading the literature critically; making notes; writing a literature review; referencing and

compiling a bibliography.

Searching the literature is the starting point of all research and is the process of exploring all sources of published

information. This information, whether it is textual, statistical or diagrammatic, is secondary. Searching the literature

will enable you to:

ascertain what has been published and by whom

increase your knowledge and understanding of the topic

assess whether the research topic is feasible

possibly narrow the topic down

refine or amend the research questions

give you some ideas about the approaches, methods and analysis.

Getting started

You should aim to start your literature search as soon as possible. Everything associated with research takes longer

than planned and searching the literature is no exception. At the very outset, you need to undertake the following:

Define the scope of the research and set parameters, for example, by time, geography, industry, or sector of

an industry. The more precise you can be the easier the task. Try and identify key words; include alternative

spellings of these words or synonyms (words that have similar meanings). For example, if you are

researching 'wage bargaining' you should also look at 'industrial relations' and 'conflict theory'.

Conduct searches on these key words using a variety of sources. Only collect articles and books, etc., which

are relevant, for example, in terms of subject matter, methodology, theoretical discussion, research

instruments, etc

Having found one reference in one source, use the references in that to guide you to others. It is important

to try and get the most recent literature first and work back in time.

Sources of published information

Most students underestimate the number of sources and the amount of material available. The basic problems are:

knowing what is available

where to find it.

We can classify sources as:

paper-based sources - books, journals, periodicals, abstracts, indexes, directories, research reports,

conference papers, market reports, annual reports, organisations' internal records, newspapers, and

magazines

electronic sources - on-line databases, Internet, off-line databases (CD-ROMs), videos and broadcasts.

Technical skills

To find the appropriate information, the researcher needs many technical skills. Consider the following:

Do you know the Dewey classification system?

Can you access data from on-line databases?

Can you access data from off-line databases?

Do you know what government publications are held in your university library?

What market intelligence reports are there?

etc.

 

It is fundamentally important that you keep a record of the details of any text you read, whether it is a book, article or

information on the Internet. Should you wish to return to the material some time later you will know where to look.

Finding information is hard enough, finding it again is even harder!

Keeping a record of a text you have read can be done in a variety of ways - using loose sheets of paper, a notebook,

index cards, or electronically with a spreadsheet, database or even a personal organiser.

Index cards

One way of keeping a record is to build a card index system. It has the following advantages:

They are easy to sort, for example, into topic areas, alphabetical order, etc.

They can be colour-coded, for example, by subject.

You can insert cards as you read more.

You can carry them around with you.

They stand up to wear and tear.

You can check texts and information as you find it.

You are building a bibliography as you go; you will need this eventually and thus ultimately saves time.

Having found a text, note the following basic details immediately on the card:

1. Book or article title.

2. Author's surname and forename and any subsequent initials.

3. Year of publication.

4. If a book: book title, edition if 2nd, 3rd, etc., place of publication, publisher, chapter or page numbers.

5. If an article: the article's title, journal name, volume number, issue or part number, page numbers.

6. Library catalogue number (Dewey decimal number).

7. Precise details when found, also location, floor, room and shelf.

Example

The completed front of index cards for a book and an article in a journal are shown below.

Book/journal:

Book

Author:

Kerlinger, F.N.

Date:

1986

Title:

Foundations of Behavioural Research

Edition:

3rd

Place:

London

Publisher:

CBS Publishing, Japan

Location:

St Mary's Road LRC

Floor A3, Shelf 4

Date found:

20 October 1999

Classification number:

150.72/KER

 

Book/journal:

Journal

Author:

Brown, M.

Date:

1996

Article title:

Environmental policy in the hotel sector

Journal title:

International Journal of Contemporary Hospitality Management

Volume/Number:

Vol. 8, No. 3

Page numbers:

18-23

Location:

St Mary's Road LRC

Floor B2, Periodicals

Date found:

20 October 1999

 

 

The SQ3R strategy, which stands for:

is an approach not just for reading a text but for reading a text effectively, efficiently and critically. It has been found to

be particularly useful because it can be applied to different texts (for example, textbook, article or dissertation) and

the type of reading required (for example, overview of the text or detailed reading).

Survey

Most people who are given a new book start reading the text without making any attempt to gain an overview of

whether the book or article is worth spending time on. It is important to survey the whole before you attempt to read

the parts. Here are a few suggestions about how you should gain this overview. To begin with, consider the start and

the end of the book:

Title page - This can give the answer to some important questions: the general subject area, the level of

approach, the author's name and qualifications, the year of publication.

Table of contents - This gives you information about the scope of the book, the way it is organised, and the

main chapters and sections. It is a very valuable source of information in signposting the issues raised.

Preface - The preface, author's remarks, foreword or introduction, will often give you an overview of the

author's intentions and assumptions. This can be particularly valuable when there are different views about

a topic.

Index - Turn to the back of the book and glance through the index; this can give a more detailed source of

information about the book. It is particularly useful if you are looking for references on a specific topic.

Bibliography - Is there a bibliography (some texts call it References)? How many references are given?

Many or few?

Glossary - Is there a list defining key words used in the text? Would it be useful to know any definitions

before you start reading?

Appendices - Are there any appendices? Consider when these might be useful?

Leaf through the book - Turn each page, looking at section headings, any chapter summaries or key

words. Any pictures or figures and tables can be useful.

First and last chapters - For a journal article especially, it is useful to read the first and last paragraphs.

Often these will summarise the key points made. Some of the better textbooks will have chapter summaries

or a list of key points or concepts developed. Headings and sub-headings are also valuable in setting the

scene.

Surveying a chapter - Having gained an overview of the book, you may wish to look at one chapter in

greater depth. Even if you are just dipping into a particular chapter in preparation for a tutorial you should

adopt the same approach.

This survey should take no more than 10 minutes. Investing in this time pays good dividends. You will find that with

practice even a few minutes will give you an overall idea of the content and layout.

Question

The survey process will have helped you to develop further the questions that you want answered. Never start

detailed reading until you have some clear questions requiring an answer. Questioning is a vital stage in assisting

with recall. These questions will vary according to your tasks, but some issues are probably common.

Example

How does this text fit in with what I already know?

Who is telling me this?

Does the author offer evidence to support or contradict the views being presented? Is the piece being

argued from only one point of view?

Is the language used reasoned and objective? Or is it emotive?

What theoretical perspectives does the author apply?

Is the material up-to-date?

What can I do with the information?

The key point is that questioning helps you to read with a purpose. It helps you to be aware of the issues being

discussed.

Read

Reading in detail is the third step - it is not, as many students seem to think, the one and only stage! In planning your

reading remember some key points:

Reading with purpose is more effective than reading without purpose.

Make reading an active process - in other words, you are actively in search of information.

Divide your reading into manageable sections. Do not try and read too much at once.

Make notes after you have read a particular section. Do not try and make notes as you go. This interferes

with your ability to question and concentrate.

Look for the idea behind each paragraph. There should be one sentence in the paragraph that sums up the

key idea.

Look for the author's plan. What is the main idea? How does the author develop the idea behind the book,

through the chapters, sections and paragraphs?

Read the passage again - you may find it easier to return to the book the next day. Difficult concepts will

then appear less difficult. Do not expect to understand everything on the first reading.

Recall

With the SQ3R method, studying does not end with reading the text. You may understand the text, but will you be

able to recall it? Most people forget 50% of a book within seconds of putting it down!

Organised recall strategies will improve your learning in a number of ways:

You will concentrate because you have a task ahead of you.

You can correct memory lapses, thereby making your learning more effective.

You will be active during the learning process. Again, this will make you much more effective.

The key recall steps are:

Depending on the text, try to recall the key points made by each paragraph within a section, preferably in

your own words.

Jot down the key words.

It can be useful to try and recall the main explanatory sentence in each paragraph.

Review

Always check the accuracy of what you recall by viewing again the material you have studied. The best way of doing

this is to repeat the process - survey, question, re-read, recall.

 

There are two particular aspects to take into account in note making:

1. What are the contents of the notes?

2. Where do you record the notes?

Contents of the notes

It is up to you what you record and the depth or detail contained in your notes. You can record key words, chapter

headings, a summary (which may be provided in the text), quotations, personal opinions, etc. For example, the

following is a 62-word summary of a book written by Carl Boggs in 1980 called Gramsci's Marxism.

"Straightforward introduction. Easy to read, logical in its structure and presentation of Gramsci's work. Well articulated

background of Marxism and the philosophy of Praxis. Excellent in accessing the notion of ideological hegemony and

its role in the class struggle. Makes Gramsci and his work understandable and applicable to modern capitalism by

taking the key concepts and exploring and applying them in context."

Where do you keep the notes?

Some possibilities of the place where you keep your notes include the following:

1. Use the reverse side of the index card if the comments are short.

2. Use loose sheets of paper, a notebook, or a photocopy of the material. Whichever of these you use you

should cross-reference to the index card.

3. If you use notebooks or paper, do not write on the reverse side as you may wish to cut it up and re-order the

material, for example, topic-by-topic.

4. On photocopies you can use a highlighter pen for key words, sentences, quotations, etc.

 

You have to do this twice - once in your proposal and once in your final dissertation. In your proposal, the literature

review is rather like an essay and should discuss the key points of relevant literature that you have found on the topic

identified in your title. This section is likely to form the bulk of the proposal, and the committee will be looking for

evidence that you have found some key and relevant texts in the topic area, have read them, identified some key

themes and issues and can discuss them with a level of understanding. It is not expected that you have undertaken a

complete literature search but it is expected that you have made a start and read around the subject. You cannot

develop your research questions or hypotheses unless you have done this. It should be 600-800 words long and end

with a list of full references. A literature review is not done book by book (or source by source) but is integrated and

written up under key themes and issues that may or may not have headings.

In your dissertation, the literature review is much more substantial but the same principles apply. You should use an

integrated style presented under clear and logical headings. Most of what follows is relevant to both the proposal and

to the dissertation - it is really a matter of scale that differentiates them.

A literature review is a written summary of the findings from the literature search. Its purpose is to provide proof of

scholarship - to show that you know the literature and you have the intellectual capacity to read it, develop the

theoretical argument and be able to give a critical, constructive analysis of that literature.

Writing a review is a demanding exercise. You will not get it right first or second time. Much material that you have

found and recorded will not be used. Editing and discarding information is heartbreaking but essential.

Some tips on writing up the literature

Start writing as soon as possible.

Select and cite only relevant material - you do not need to include a mention of everything you read.

Group the material into categories and comment upon the most important features.

Be critical. An uncritical review tends to be descriptive, where everything merits a one paragraph entry, such

as 'Smith (1985) found...; Jones (1987) found....' A critical review shows that you have studied existing work

in the field with insight by pointing out the strengths and weaknesses; by comparing the results of different

studies; and by evaluating theories, etc., with reference to your own study.

Use quotations to illustrate a point and add an extra dimension to your argument.

STRUCTURING A LITERATURE REVIEW

It is often difficult to decide how to organise the huge amount of information you have collected. The structure of each

dissertation will be different but there are some general principles and these are really the guidelines you should use

for any piece of academic writing. The dissertation is just much longer than most essays or other pieces of work.

Introduction to the literature review

There should be an introduction to your literature that signposts the content by stating the approach you will

take and puts forward the central ideas and purpose of the literature review. It 'sets the scene' and provides

a 'map' of where the literature review is going to take the reader and why. It should also stimulate interest. It

is likely that this part will have to be written after the main sections. It is not likely to be more than half a page

long but needs to be carefully crafted.

Main part

This should consist of discrete sections arranged in a logical order. Unlike an essay where paragraphs are

simply arranged in order without headings, a dissertation needs clear headings due to the size of the work.

Headings help the reader, and you, the writer, to keep on track. Each section should be devoted to one topic

or theme, and each paragraph within each section should confine itself to a single idea. The first sentence of

a paragraph should indicate what the paragraph is about in some way and then move on to develop that

idea supported by evidence and examples. Avoid having a lot of short paragraphs of one or two sentences.

Also avoid lots of lists. This may be appropriate for report and business-style writing but is not suitable for

essays or dissertations.

The key concept here is of developing an argument, and your tutors will be looking for the following:

o The writing shows a sense of purpose and direction, as though the writer knows where he or she is

going and is leading the reader there step-by-step.

o There is a definite central idea with reasons for it and evidence to back it up and support it.

o The writing may present a 'case' for a certain viewpoint.

o The writing is logical with ideas or events linked together in a logical sequence.

o The ideas are put together in a way that is clear to the writer and to the reader.

Conclusions

At the end of your literature review you must summarise and draw conclusions about the key points in your

writing. There needs to be a sense of completion to the whole piece; you need to 'round off' rather than just

stop abruptly. At this stage, you will discover just how much of your writing is descriptive and how much is

critical. It is only when you are writing using analysis and evaluation that you are likely to be able to draw

conclusions!

STYLES OF WRITING

There are many different ways of looking at academic writing styles and one way is to try and identify which of the

following styles you are using. All styles have their place but you need to be wary of spending too much time in your

dissertation on the first two.

Chronological writing

This style of writing looks at events over a period of time and relates them chronologically or in date order. Thus,

historical texts would follow this style. Often students want to give the historical background to their research area

and this is often appropriate. However, be careful not to overdo this. If your research question relates to the 'here and

now' (and most do), then it is not appropriate or relevant to have three-quarters of your literature review giving the

historical background. It may be appropriate for you to read it so that you understand the context of your study, but it

is usually appropriate to confine yourself to a brief summary of the key points, or use this material in the introductory

chapter to the dissertation.

An example of this would be a student who wanted to research into whether the media treats women and men

athletes the same in terms of sports reporting. There is a vast amount of literature on the historical inequalities in

sport which make fascinating reading and could perhaps be mentioned. However, this student would be much better

advised to concentrate the bulk of their literature on athletics, sports coverage in the media, gender bias in media,

and content analysis of gender bias.

Descriptive writing

It is likely that your literature review will contain descriptive writing which is appropriate for outlining characteristics,

models, theories and diagrams, etc. However, beware of this style! If all your writing is descriptive then you will not

show that you have the ability to critically review the literature and, therefore, you need to include some of the

following styles.

Cause and effect writing

Here you identify the link between one activity and another or one variable and another. What happened? Why did

something happen? What were the consequences? This may be an appropriate style of writing in your literature

review and is also useful for writing up your findings.

Compare and contrast writing (theme-by-theme)

Here you take two or more concepts or ideas and compare them (looking for similarities) and contrast them (looking

for differences). This often occurs in an essay where you may be specifically asked to do this. In a literature review,

you may have identified a number of models or theories and want to compare and contrast them in order to develop a

rationale for which one to use as the basis for your dissertation, or to help you construct a model on the best or most

appropriate aspects of each.

Summarising writing

Sometimes you are asked to summarise something for a piece of work, but this style is particularly appropriate for

making notes on key topics, summarising the key points. When doing this, think about why you wish to include this

idea and how it fits in with your overall dissertation. You may need to summarise the key points of someone else's

work in your dissertation. Summaries are often descriptive.

Analytical writing

Analysis means breaking things down into their constituent parts. For example, if you were to analyse milk you would

find, in simple terms, that it consisted of a large amount of water, protein, sugar and various minerals and vitamins. In

academic writing this means you have to 'unpick' or 'tease out' a concept in order to answer questions such as:

Evaluative writing

In order to evaluate, you have to make a judgement or put a 'value' on something. Is it 'good' or 'appropriate for the

purpose', or 'inadequate' or 'lacking evidence', or 'useful' and so on? To do this, almost certainly you will first have

analysed the data in order to make your judgement. Analysis and evaluation go hand-in-hand. You then have to go

one step further and say why something is 'useful', or whatever, and give reasons for your judgement.

It is quite likely that your dissertation will contain most, if not all, of the above styles of writing. They apply not only to

writing up the literature but to all sections of your work. There is also some overlap between them. For example,

chronological writing could also encompass any of the other styles although it is often used descriptively - first this

happened, then that happened. Your tutors will be looking for you to use a range of writing skills in your dissertation

as appropriate, but make sure that you minimise the descriptive writing and try to develop the other styles.

Language and writing

Note some key points about language:

Keep it simple and clear.

Do not use a long word when a short one will do.

Try to have an average sentence length of 15-20 words; long sentences are hard to follow.

Always use the 'third person'. Do not use words such as 'I', 'me', 'my'. For example, write, 'It could be

considered that', and not, 'I think that'.

Check spelling and grammar; if this is a weak area then improve by asking for feedback from your tutor;

reading texts on grammar, punctuation and spelling, etc.

Try to write in a way that will be interesting to read. Your tutors have a lot of dissertations to mark and one

that is interesting and enjoyable to read will be memorable.

You need to show that in addition to describing something you can interpret, apply, evaluate and reach

conclusions. Some useful words and phrases are given below to help you identify when you are doing what!

 

 

 

 

Writing is a skill like any other - it takes practice. It is likely that your skills in this area, after studying for two or three

years, will already be quite good. However, if you are returning to study or are much more used to writing in a report

format, then you may find it necessary to do quite a lot of work on your writing skills. This will be useful for all

modules, not just the dissertation.

 

 

One of the common features of a good essay or other piece of academic work is the appropriate use of references

and quotations. In both cases, they will add scholarly weight to your work, but they must be properly dealt with.

Any idea which is not your own but comes from someone else must be acknowledged in your writing. This

acknowledgement of the source of the information is called a reference or citation.

Referencing aims to:

help the reader to distinguish between your ideas and those from other sources

give authority to ideas that you are putting forward by showing that they have independent theoretical

support

enable readers to check and follow up for themselves the authors you have read

indicate in a concise fashion the existence of the body of published work that you have used in preparing

your essay, report, etc.

avoid the accusations of plagiarism.

You will lose marks if you do not reference correctly.

Using references within your text

There are many ways to give a reference used within the text. Perhaps the most popular method, because it is the

simplest, is the Harvard System - where the author's surname is followed by the year of publication. This is also

known as the 'author-date' system and is the method we advise you to use in all your writings whilst studying on this

programme.

As well as the general aims of references given above, references within the text are specifically used to:

provide support for ideas (see 'a' below)

cite supporters of ideas (see 'b' below)

acknowledge the source of ideas (see 'c' below)

establish facts (see 'd' below).

The standard ways of giving a reference within the text using the Harvard system, and the various possibilities that

can occur, are illustrated in the following examples:

If there is one author who is the subject of the sentence (such as 'a' and 'b' above) the date of publication is put in

brackets (parenthesises) after the surname.

If the reference to both the author and the date of publication are not a main part of the sentence (as in 'c' and 'd'

above) add them parenthetically at the end of the sentence.

If you refer to Smith again within the same paragraph, there is no need to quote the year. You can say, for example:

As Smith argues...

or

Smith's position on this is...

Here the reference to Smith indicates that you are still presenting the ideas of his 1997 article. If, in another

paragraph, you wish to refer to Smith again, revert to specifying the name and the date - Smith (1997)

Where there are two or more co-authors, all names are given when first cited.

For more than one author, place the authors in chronological order.

If the work is the product of an organisation and does not carry an individual author's name, the name of the

organisation is used:

Organisation:

In a survey of households in the UK in 1997, it was found that 80% of them had a washing machine (NOS 1999).

If you have read an article by Elliott written in 1996 in a book by Kitson and Campbell that was written in 1998, cite

the author who wrote the article (Elliott) not the author of the book in which you found the material (Kitson and

Campbell).

Quotations:

You want to quote only when it is especially important for your reader to see and appreciate the precise wording of

the original. You may choose to do this to:

provide the reader with the original when you are discussing the text in detail

illustrate a point precisely

discuss interpretations of a well-known authority

respect the wording of the original when the impact would be lost if you tried to explain it or paraphrase it.

Quotations should be directly quoted, using the exact words, punctuation and spelling of the original author

irrespective of the source. A specific quotation from a text should always be identified with its page number after the

date of publication. A colon separates the year and the page number. All quotations should be enclosed within

speech marks. It is common to italicise the quotation as well.

...can be included in the main text.

Longer quotations should be started on a new line and indented further from the left-hand margin than the main text.

It is not appropriate to put long passages in quotation marks. For an extended citation, you should summarise the

material in your own words and give the appropriate reference. As a very rough guide, you would not expect to use

more than one or two sentences in quotes on each page of your text.

Bibliography

A bibliography is a list of all references, whether cited or not in your work, which have been consulted in the

preparation of the work. It should be possible to see from the bibliography, which texts are books and which are

articles. Unfortunately, there are many variations in bibliographic styles.

The variations are based on the use of upper and lower case letters, commas and full stops, italics, bolding and

underlining, and the position of the various elements that make up the reference.

Do not devise your own system. For simplicity and consistency, the following approach to constructing and writing

a bibliography should be adhered to and is based on the Harvard System. The bibliography should:

be in alphabetical order of authors' surnames. If there is no author, the issuing organisation should be used

appear at the end of the work and not at the end of each chapter or section

be a single listing and not be sub-divided into cited references and non-cited references, or books and

journals, etc.

For a book, the order of the reference is:

author's surname, followed by the initials

year of publication in round brackets

title of the book, italicised and only the first word and proper nouns capitalised

edition number, if appropriate

place of publication followed by a colon

name of the publisher.

For an article in a journal the order is:

author's surname, followed by the initials

year of publication in round brackets

title of the article in speech marks

title of the journal in italics.

Then, if you also know:

month or date of issue, the volume number, the issue number

page number - preceded by 'p.' for a single page and 'pp.' for multiple pages.

For organisations the order is:

name of organisation

year of publication in round brackets

title of the article in speech marks.

For articles in non-academic sources:

For articles in non-academic sources, such as a newspaper or manuals, the structure and order is dependent on the

availability of detail, such as the author's name, and is a mix of the above procedures.

For a cited author quoted in another text:

cited author's surname followed by the initials

year of the cited author's publication in round brackets

title of the cited author's book (italicised) or article (speech marks)

author, year, title, location and publisher of the source text preceded by the words cited in, all enclosed in

square brackets.

For an Internet source:

The reference style for Internet sources uses a modified Harvard system:

author's surname, first name or homepage/institution/university/business name

date if available

<email address if given>

title of document

Internet address URL www.address

date site visited.

Remember that you should be able to:

cite an author (and variations) using the Harvard System

quote an author

construct a bibliography using the Harvard System

be able to differentiate between books, articles, organisations and Internet sources when listed in a

bibliography.

SUMMARY

In this unit, you have worked through the skills of searching and reviewing the literature, making notes and keeping

bibliographical records. You have also worked through some theory on writing more effectively, developing your

writing structure and style. These skills need practising and are applicable to any other modules you are studying.

Practise them and get feedback from your tutors. You should also show a sample of your draft literature review to

your supervisor who will be able to help you with these skills.

 

By now you will have a clear research question and will have read a lot of literature on your topic. Only when you

have completed these two essential first stages are you ready to think about planning your overall approach to

collecting data. Data is effectively another word for information that can be found through secondary or primary data

collection. It is important that you understand all the various ways of collecting data so that you can decide which to

use for your own research. It is worth remembering at this stage that all methods of data collection can supply

quantitative data (numbers and statistics) or qualitative data (usually words or text).

 

All methods of data collection can supply quantitative data (numbers, statistics or financial) or qualitative data (usually

words or text). Quantitative data may often be presented in tabular or graphical form. Secondary data is data that has

already been collected by someone else for a different purpose to yours. For example, this could mean using:

data collected by a hotel on its customers through its guest history system

data supplied by a marketing organisation

annual company reports

government statistics.

Secondary data can be used in different ways:

You can simply report the data in its original format. If so, then it is most likely that the place for this data will

be in your main introduction or literature review as support or evidence for your argument.

You can do something with the data. If you use it (analyse it or re-interpret it) for a different purpose to the

original then the most likely place would be in the ‘Analysis of findings’ section of your dissertation. A good

example of this usage was the work on suicide carried out by Durkheim. He took the official suicide statistics

of different countries (recorded by coroners or their equivalent) and analysed them to see if he could identify

variables that would mean that some people are more likely to commit suicide than others. He found, for

example, that Catholics were less likely to commit suicide than Protestants. In this way, he took data that

had been collected for quite a different purpose and used it in his own study – but he had to do a lot of

comparisons and statistical correlations himself in order to analyse the data. (See Haralambos, 1995, for

details of Durkheim’s work).

Most research requires the collection of primary data (data that you collect at first hand), and this is what students

concentrate on. Unfortunately, many dissertations do not include secondary data in their findings section although it is

perfectly acceptable to do so, providing you have analysed it. It is always a good idea to use data collected by

someone else if it exists – it may be on a much larger scale than you could hope to collect and could contribute to

your findings considerably.

As secondary data has been collected for a different purpose to yours, you should treat it with care. The basic

questions you should ask are:

Where has the data come from?

Does it cover the correct geographical location?

Is it current (not too out of date)?

If you are going to combine with other data are the data the same (for example, units, time, etc.)?

If you are going to compare with other data are you comparing like with like?

Thus you should make a detailed examination of the following:

Title (for example, the time period that the data refers to and the geographical coverage).

Units of the data.

Source (some secondary data is already secondary data).

Column and row headings, if presented in tabular form.

Definitions and abbreviations, for example, what does SIC stand for? For example, how is ‘small’ defined in

the phrase ‘small hotel’? Is ‘small’ based on the number of rooms, value of sales, number of employees,

profit, turnover, square metres of space, etc., and do different sources use the word ‘small’ in different

ways? Even if the same unit of measurement is used, there still could be problems. For example, in Norway,

firms with 200-499 employees are defined as ‘medium’, whereas in the USA firms with less than 500

employees are defined as ‘small’.

There are many sources of data and most people tend to underestimate the number of sources and the amount of

data within each of these sources.

Sources can be classified as:

paper-based sources – books, journals, periodicals, abstracts, indexes, directories, research reports,

conference papers, market reports, annual reports, internal records of organisations, newspapers and

magazines

electronic sources– CD-ROMs, on-line databases, Internet, videos and broadcasts.

The main sources of qualitative and quantitative secondary data include the follwing:

Official or government sources.

Unofficial or general business sources.

The output of all publishers of non-official sources is included in the most comprehensive directory available:

Mort D. (1997) Sources of Unofficial UK Statistics 3rd Edition Aldershot: Gower

The guide lists 1,059 statistical titles and series published by 635 different organisations. It excludes one-off surveys

or market reports.

The arrangement is alphabetical by organisation with details of titles produced and contacts for further information. It

lists references to the following types of sources:

trade associations

trade and other journals

private research publishers

stockbroking firms

large company market reports

local authorities

professional bodies

academic institutions.

European Union (Community) sources.

International sources.

o Organisation for Economic Co-operation and Development (OECD)

o United Nations and related organisations.

Sources for the last two categories are many and varied. If your dissertation requires these sources you need to

conduct a more thorough search of your library and perhaps seek the assistance of the librarian.

 

In primary data collection, you collect the data yourself using methods such as interviews and questionnaires. The

key point here is that the data you collect is unique to you and your research and, until you publish, no one else has

access to it.

There are many methods of collecting primary data and the main methods include:

questionnaires

interviews

focus group interviews

observation

case-studies

diaries

critical incidents

portfolios.

Click on one of the above icons for the information in LRN format.

The primary data, which is generated by the above methods, may be qualitative in nature (usually in the form of

words) or quantitative (usually in the form of numbers or where you can make counts of words used). We briefly

outline these methods but you should also read around the various methods. A list of suggested research

methodology texts is given in your Module Study Guide but many texts on social or educational research may also be

useful and you can find them in your library.

Questionnaires

Questionnaires are a popular means of collecting data, but are difficult to design and often require many rewrites

before an acceptable questionnaire is produced.

Advantages:

Can be used as a method in its own right or as a basis for interviewing or a telephone survey.

Can be posted, e-mailed or faxed.

Can cover a large number of people or organisations.

Wide geographic coverage.

Relatively cheap.

No prior arrangements are needed.

Avoids embarrassment on the part of the respondent.

Respondent can consider responses.

Possible anonymity of respondent.

No interviewer bias.

Disadvantages:

Design problems.

Questions have to be relatively simple.

Historically low response rate (although inducements may help).

Time delay whilst waiting for responses to be returned.

Require a return deadline.

Several reminders may be required.

Assumes no literacy problems.

No control over who completes it.

Not possible to give assistance if required.

Problems with incomplete questionnaires.

Replies not spontaneous and independent of each other.

Respondent can read all questions beforehand and then decide whether to complete or not. For example,

perhaps because it is too long, too complex, uninteresting, or too personal.

Design of postal questionnaires

Theme and covering letter

The general theme of the questionnaire should be made explicit in a covering letter. You should state who you are;

why the data is required; give, if necessary, an assurance of confidentiality and/or anonymity; and contact number

and address or telephone number. This ensures that the respondents know what they are committing themselves to,

and also that they understand the context of their replies. If possible, you should offer an estimate of the completion

time. Instructions for return should be included with the return date made obvious. For example: ‘It would be

appreciated if you could return the completed questionnaire by... if at all possible’.

Instructions for completion

You need to provide clear and unambiguous instructions for completion. Within most questionnaires these are

general instructions and specific instructions for particular question structures. It is usually best to separate these,

supplying the general instructions as a preamble to the questionnaire, but leaving the specific instructions until the

questions to which they apply. The response method should be indicated (circle, tick, cross, etc.). Wherever possible,

and certainly if a slightly unfamiliar response system is employed, you should give an example.

Appearance

Appearance is usually the first feature of the questionnaire to which the recipient reacts. A neat and professional look

will encourage further consideration of your request, increasing your response rate. In addition, careful thought to

layout should help your analysis. There are a number of simple rules to help improve questionnaire appearance:

Liberal spacing makes the reading easier.

Photo-reduction can produce more space without reducing content.

Consistent positioning of response boxes, usually to the right, speeds up completion and also avoids

inadvertent omission of responses.

Choose the font style to maximise legibility.

Differentiate between instructions and questions. Either lower case and capitals can be used, or responses

can be boxed.

Length

There may be a strong temptation to include any vaguely interesting questions, but you should resist this at all costs.

Excessive size can only reduce response rates. If a long questionnaire is necessary, then you must give even more

thought to appearance. It is best to leave pages unnumbered; for respondents to flick to the end and see ‘page 27’

can be very disconcerting!

Order

Probably the most crucial stage in questionnaire response is the beginning. Once the respondents have started to

complete the questions they will normally finish the task, unless it is very long or difficult. Consequently, you need to

select the opening questions with care. Usually the best approach is to ask for biographical details first, as the

respondents should know all the answers without much thought. Another benefit is that an easy start provides

practice in answering questions.

Once the introduction has been achieved the subsequent order will depend on many considerations. You should be

aware of the varying importance of different questions. Essential information should appear early, just in case the

questionnaire is not completed. For the same reasons, relatively unimportant questions can be placed towards the

end. If questions are likely to provoke the respondent and remain unanswered, these too are best left until the end, in

the hope of obtaining answers to everything else.

Coding

If analysis of the results is to be carried out using a statistical package or spreadsheet it is advisable to code non-

numerical responses when designing the questionnaire, rather than trying to code the responses when they are

returned. An example of coding is:

Male [   ]

Female [   ]

1

2

The coded responses (1 or 2) are then used for the analysis.

Thank you

Respondents to questionnaires rarely benefit personally from their efforts and the least the researcher can do is to

thank them. Even though the covering letter will express appreciation for the help given, it is also a nice gesture to

finish the questionnaire with a further thank you.

Questions

Keep the questions short, simple and to the point; avoid all unnecessary words.

Use words and phrases that are unambiguous and familiar to the respondent. For example, ‘dinner’ has a

number of different interpretations; use an alternative expression such as ‘evening meal’.

Only ask questions that the respondent can answer. Hypothetical questions should be avoided. Avoid

calculations and questions that require a lot of memory work, for example, ‘How many people stayed in your

hotel last year?’

Avoid loaded or leading questions that imply a certain answer. For example, by mentioning one particular

item in the question, ‘Do you agree that Colgate toothpaste is the best toothpaste?’

Vacuous words or phrases should be avoided. ‘Generally’, ‘usually’, or ‘normally’ are imprecise terms with

various meanings. They should be replaced with quantitative statements, for example, ‘at least once a

week’.

Questions should only address a single issue. For example, questions like: ‘Do you take annual holidays to

Spain?’ should be broken down into two discreet stages, firstly find out if the respondent takes an annual

holiday, and then secondly find out if they go to Spain.

Do not ask two questions in one by using ‘and’. For example, ‘Did you watch television last night and read a

newspaper?’

Avoid double negatives. For example, ‘Is it not true that you did not read a newspaper yesterday?’

Respondents may tackle a double negative by switching both negatives and then assuming that the same

answer applies. This is not necessarily valid.

State units required but do not aim for too high a degree of accuracy. For instance, use an interval rather

than an exact figure:

‘How much did you earn last year?’

Less than £10,000 [   ]

£10,000 but less than £20,000 [   ]

Avoid emotive or embarrassing words – usually connected with race, religion, politics, sex, money.

Types of questions

Closed questions

A question is asked and then a number of possible answers are provided for the respondent. The respondent selects

the answer which is appropriate. Closed questions are particularly useful in obtaining factual information:

Sex:    Male [   ] Female [   ]

Did you watch television last night?     Yes [   ] No [   ]

Some ‘Yes/No’ questions have a third category ‘Do not know’. Experience shows that as long as this alternative is not

mentioned people will make a choice. Also the phrase ‘Do not know’ is ambiguous:

Do you agree with the introduction of the EMU?

Yes [   ] No [   ] Do not know [   ]

What was your main way of travelling to the hotel? Tick one box only.

Car

[   ]

Coach

[   ]

Motor bike

[   ]

Train

[   ]

Other means, please specify

With such lists you should always include an ‘other’ category, because not all possible responses might have been

included in the list of answers.

Sometimes the respondent can select more than one from the list. However, this makes analysis difficult:

Why have you visited the historic house? Tick the relevant answer(s). You may tick as many as you like.

I enjoy visiting historic houses

[   ]

The weather was bad and I could not enjoy outdoor activities

[   ]

I have visited the house before and wished to return

[   ]

Other reason, please specify

Attitude questions

Frequently questions are asked to find out the respondents’ opinions or attitudes to a given situation. A Likert scale

provides a battery of attitude statements. The respondent then says how much they agree or disagree with each one:

Read the following statements and then indicate by a tick whether you strongly agree, agree, disagree or strongly

disagree with the statement.

 

Strongly agree

Agree

Disagree

Strongly disagree

My visit has been good value for money

 

 

 

 

There are many variations on this type of question. One variation is to have a ‘middle statement’, for example,

‘Neither agree nor disagree’. However, many respondents take this as the easy option. Only having four statements,

as above, forces the respondent into making a positive or negative choice. Another variation is to rank the various

attitude statements, however, this can cause analysis problems:

Which of these characteristics do you like about your job? Indicate the best three in order, with the best being number

1.

Varied work

[   ]

Good salary

[   ]

Opportunities for promotion

[   ]

Good working conditions

[   ]

High amount of responsibility

[   ]

Friendly colleagues

[   ]

A semantic differential scale attempts to see how strongly an attitude is held by the respondent. With these scales

double-ended terms are given to the respondents who are asked to indicate where their attitude lies on the scale

between the terms. The response can be indicated by putting a cross in a particular position or circling a number:

Work is: (circle the appropriate number)

Difficult 

1   2   3   4   5   6   7

Easy

Useless

1   2   3   4   5   6   7

Useful

Interesting

1   2   3   4   5   6   7

Boring

For summary and analysis purposes, a ‘score’ of 1 to 7 may be allocated to the seven points of the scale, thus

quantifying the various degrees of opinion expressed. This procedure has some disadvantages. It is implicitly

assumed that two people with the same strength of feeling will mark the same point on the scale. This almost

certainly will not be the case. When faced with a semantic differential scale, some people will never, as a matter of

principle, use the two end indicators of 1 and 7. Effectively, therefore, they are using a five-point scale. Also scoring

the scale 1 to 7 assumes that they represent equidistant points on the continuous spectrum of opinion. This again is

probably not true. Nevertheless, within its limitations, the semantic differential can provide a useful way of measuring

and summarising subjective opinions.

Other types of questions to determine peoples’ opinions or attitudes are:

Which one/two words best describes...?

Which of the following statements best describes...?

How much do you agree with the following statement...?

Open questions

An open question such as ‘What are the essential skills a manager should possess?’ should be used as an adjunct to

the main theme of the questionnaire and could allow the respondent to elaborate upon an earlier more specific

question. Open questions inserted at the end of major sections, or at the end of the questionnaire, can act as safety

valves, and possibly offer additional information. However, they should not be used to introduce a section since there

is a high risk of influencing later responses. The main problem of open questions is that many different answers have

to be summarised and possibly coded.

Testing – pilot survey

Questionnaire design is fraught with difficulties and problems. A number of rewrites will be necessary, together with

refinement and rethinks on a regular basis. Do not assume that you will write the questionnaire accurately and

perfectly at the first attempt. If poorly designed, you will collect inappropriate or inaccurate data and good analysis

cannot then rectify the situation.

To refine the questionnaire, you need to conduct a pilot survey. This is a small-scale trial prior to the main survey that

tests all your question planning. Amendments to questions can be made. After making some amendments, the new

version would be re-tested. If this re-test produces more changes, another pilot would be undertaken and so on. For

example, perhaps responses to open-ended questions become closed; questions which are all answered the same

way can be omitted; difficult words replaced, etc.

It is usual to pilot the questionnaires personally so that the respondent can be observed and questioned if necessary.

By timing each question, you can identify any questions that appear too difficult, and you can also obtain a reliable

estimate of the anticipated completion time for inclusion in the covering letter. The result can also be use to test the

coding and analytical procedures to be performed later.

Distribution and return

The questionnaire should be checked for completeness to ensure that all pages are present and that none is blank or

illegible. It is usual to supply a prepaid addressed envelope for the return of the questionnaire. You need to explain

this in the covering letter and reinforce it at the end of the questionnaire, after the ‘Thank you’.

Finally, many organisations are approached continually for information. Many, as a matter of course, will not respond

in a positive way.

Interviews

Interviewing is a technique that is primarily used to gain an understanding of the underlying reasons and motivations

for people’s attitudes, preferences or behaviour. Interviews can be undertaken on a personal one-to-one basis or in a

group. They can be conducted at work, at home, in the street or in a shopping centre, or some other agreed location.

Personal interview

Advantages:

Serious approach by respondent resulting in accurate information.

Good response rate.

Completed and immediate.

Possible in-depth questions.

Interviewer in control and can give help if there is a problem.

Can investigate motives and feelings.

Can use recording equipment.

Characteristics of respondent assessed – tone of voice, facial expression, hesitation, etc.

Can use props.

If one interviewer used, uniformity of approach.

Used to pilot other methods.

Disadvantages:

Need to set up interviews.

Time consuming.

Geographic limitations.

Can be expensive.

Normally need a set of questions.

Respondent bias – tendency to please or impress, create false personal image, or end interview quickly.

Embarrassment possible if personal questions.

Transcription and analysis can present problems – subjectivity.

If many interviewers, training required.

Types of interview

Structured:

Based on a carefully worded interview schedule.

Frequently require short answers with the answers being ticked off.

Useful when there are a lot of questions which are not particularly contentious or thought provoking.

Respondent may become irritated by having to give over-simplified answers.

Semi-structured

The interview is focused by asking certain questions but with scope for the respondent to express him or herself at

length.

Unstructured

This also called an in-depth interview. The interviewer begins by asking a general question. The interviewer then

encourages the respondent to talk freely. The interviewer uses an unstructured format, the subsequent direction of

the interview being determined by the respondent’s initial reply. The interviewer then probes for elaboration – ‘Why do

you say that?’ or, ‘That’s interesting, tell me more’ or, ‘Would you like to add anything else?’ being typical probes.

The following section is a step-by-step guide to conducting an interview. You should remember that all situations are

different and therefore you may need refinements to the approach.

Planning an interview:

List the areas in which you require information.

Decide on type of interview.

Transform areas into actual questions.

Try them out on a friend or relative.

Make an appointment with respondent(s) – discussing details of why and how long.

Try and fix a venue and time when you will not be disturbed.

Conducting an interview:

Personally

–

arrive on time be smart smile employ good manners find a balance between friendliness and objectivity.

At the start

–

introduce yourself re-confirm the purpose assure confidentiality – if relevant specify what will happen to the data.

The questions

–

speak slowly in a soft, yet audible tone of voice control your body language know the questions and topic ask all the

questions.

Responses

–

recorded as you go on questionnaire written verbatim, but slow and time-consuming summarised by you taped –

agree beforehand – have alternative method if not acceptable consider effect on respondent’s answers proper

equipment in good working order sufficient tapes and batteries minimum of background noise.

At the end

–

ask if the respondent would like to give further details about anything or any questions about the research thank

them.

Telephone interview

This is an alternative form of interview to the personal, face-to-face interview.

Advantages:

Relatively cheap.

Quick.

Can cover reasonably large numbers of people or organisations.

Wide geographic coverage.

High response rate – keep going till the required number.

No waiting.

Spontaneous response.

Help can be given to the respondent.

Can tape answers.

Disadvantages:

Often connected with selling.

Questionnaire required.

Not everyone has a telephone.

Repeat calls are inevitable – average 2.5 calls to get someone.

Time is wasted.

Straightforward questions are required.

Respondent has little time to think.

Cannot use visual aids.

Can cause irritation.

Good telephone manner is required.

Question of authority.

Getting started

Locate the respondent:

o Repeat calls may be necessary especially if you are trying to contact people in organisations where

you may have to go through secretaries.

o You may not know an individual’s name or title – so there is the possibility of interviewing the wrong

person.

o You can send an advance letter informing the respondent that you will be telephoning. This can

explain the purpose of the research.

Getting them to agree to take part:

o You need to state concisely the purpose of the call – scripted and similar to the introductory letter of

a postal questionnaire.

o Respondents will normally listen to this introduction before they decide to co-operate or refuse.

o When contact is made respondents may have questions or raise objections about why they could

not participate. You should be prepared for these.

Ensuring quality

Quality of questionnaire – follows the principles of questionnaire design. However, it must be easy to

move through as you cannot have long silences on the telephone.

Ability of interviewer – follows the principles of face-to-face interviewing.

Smooth implementation

Interview schedule – each interview schedule should have a cover page with number, name and address.

The cover sheet should make provision to record which call it is, the date and time, the interviewer, the

outcome of the call and space to note down specific times at which a call-back has been arranged. Space

should be provided to record the final outcome of the call – was an interview refused, contact never made,

number disconnected, etc.

Procedure for call-backs – a system for call-backs needs to be implemented. Interview schedules should

be sorted according to their status: weekday call-back, evening call-back, weekend call-back, specific time

call-back.

Comparison of postal, telephone and personal interview surveys

The table below compares the three common methods of postal, telephone and interview surveys – it might help you

to decide which one to use.

 

Postal survey

Telephone survey

Personal interview

Cost (assuming a good response rate)

Often lowest

Usually in-between

Usually highest

Ability to probe

No personal contact or observation

Some chance for gathering additional data through elaboration on questions, but no personal observation

Greatest opportunity for observation, building rapport, and additional probing

Respondent ability to complete at own convenience

Yes

Perhaps, but usually no

Perhaps, if interview time is prearranged with respondent

Interview bias

No chance

Some, perhaps due to voice inflection

Greatest chance

Ability to decide who actually responds to the questions

Least

Some

Greatest

Impersonality

Greatest

Some due to lack of face-to-face contact

Least

Complex questions

Least suitable

Somewhat suitable

More suitable

Visual aids

Little opportunity

No opportunity

Greatest opportunity

Potential negative respondent reaction

‘Junk mail’

‘Junk calls’

Invasion of privacy

Interviewer control over interview environment

Least

Some in selection of time to call

Greatest

Time lag between soliciting and receiving response

Greatest

Least

May be considerable if a large area involved

Suitable types of questions

Simple, mostly dichotomous (yes/no) and multiple choice

Some opportunity for open-ended questions especially if interview is recorded

Greatest opportunity for open-ended questions

Requirement for technical skills in conducting interview

Least

Medium

Greatest

Response rate

Low

Usually high

High

Table 3.1: Comparison of the three common methods of surveys

Focus group interviews

A focus group is an interview conducted by a trained moderator in a non-structured and natural manner with a small

group of respondents. The moderator leads the discussion. The main purpose of focus groups is to gain insights by

listening to a group of people from the appropriate target market talk about specific issues of interest.

Observation

Observation involves recording the behavioural patterns of people, objects and events in a systematic manner.

Observational methods may be:

structured or unstructured

disguised or undisguised

natural or contrived

personal

mechanical

non-participant

participant, with the participant taking a number of different roles.

Structured or unstructured

In structured observation, the researcher specifies in detail what is to be observed and how the measurements are

to be recorded. It is appropriate when the problem is clearly defined and the information needed is specified.

In unstructured observation, the researcher monitors all aspects of the phenomenon that seem relevant. It is

appropriate when the problem has yet to be formulated precisely and flexibility is needed in observation to identify

key components of the problem and to develop hypotheses. The potential for bias is high. Observation findings

should be treated as hypotheses to be tested rather than as conclusive findings.

Disguised or undisguised

In disguised observation, respondents are unaware they are being observed and thus behave naturally. Disguise is

achieved, for example, by hiding, or using hidden equipment or people disguised as shoppers.

In undisguised observation, respondents are aware they are being observed. There is a danger of the Hawthorne

effect – people behave differently when being observed.

Natural or contrived

Natural observation involves observing behaviour as it takes place in the environment, for example, eating

hamburgers in a fast food outlet.

In contrived observation, the respondents’ behaviour is observed in an artificial environment, for example, a food

tasting session.

Personal

In personal observation, a researcher observes actual behaviour as it occurs. The observer may or may not normally

attempt to control or manipulate the phenomenon being observed. The observer merely records what takes place.

Mechanical

Mechanical devices (video, closed circuit television) record what is being observed. These devices may or may not

require the respondent’s direct participation. They are used for continuously recording on-going behaviour.

Non-participant

The observer does not normally question or communicate with the people being observed. He or she does not

participate.

Participant

In participant observation, the researcher becomes, or is, part of the group that is being investigated. Participant

observation has its roots in ethnographic studies (study of man and races) where researchers would live in tribal

villages, attempting to understand the customs and practices of that culture. It has a very extensive literature,

particularly in sociology (development, nature and laws of human society) and anthropology (physiological and

psychological study of man). Organisations can be viewed as ‘tribes’ with their own customs and practices.

The role of the participant observer is not simple. There are different ways of classifying the role:

Researcher as employee.

Researcher as an explicit role.

Interrupted involvement.

Observation alone.

Researcher as employee

The researcher works within the organisation alongside other employees, effectively as one of them. The role of the

researcher may or may not be explicit and this will have implications for the extent to which he or she will be able to

move around and gather information and perspectives from other sources. This role is appropriate when the

researcher needs to become totally immersed and experience the work or situation at first hand.

There are a number of dilemmas. Do you tell management and the unions? Friendships may compromise the

research. What are the ethics of the process? Can anonymity be maintained? Skill and competence to undertake the

work may be required. The research may be over a long period of time.

Researcher as an explicit role

The researcher is present every day over a period of time, but entry is negotiated in advance with management and

preferably with employees as well. The individual is quite clearly in the role of a researcher who can move around,

observe, interview and participate in the work as appropriate. This type of role is the most favoured, as it provides

many of the insights that the complete observer would gain, whilst offering much greater flexibility without the ethical

problems that deception entails.

Interrupted involvement

The researcher is present sporadically over a period of time, for example, moving in and out of the organisation to

deal with other work or to conduct interviews with, or observations of, different people across a number of different

organisations. It rarely involves much participation in the work.

Observation alone

The observer role is often disliked by employees since it appears to be ‘eavesdropping’. The inevitable detachment

prevents the degree of trust and friendship forming between the researcher and respondent, which is an important

component in other methods.

Choice of roles

The role adopted depends on the following:

Purpose of the research: Does the research require continued longitudinal involvement (long period of time),

or will in-depth interviews, for example, conducted over time give the type of insights required?

Cost of the research: To what extent can the researcher afford to be committed for extended periods of

time? Are there additional costs such as training?

The extent to which access can be gained: Gaining access where the role of the researcher is either explicit

or covert can be difficult, and may take time.

The extent to which the researcher would be comfortable in the role: If the researcher intends to keep his

identity concealed, will he or she also feel able to develop the type of trusting relationships that are

important? What are the ethical issues?

The amount of time the researcher has at his disposal: Some methods involve a considerable amount of

time. If time is a problem alternate approaches will have to be sought.

Case-studies

The term case-study usually refers to a fairly intensive examination of a single unit such as a person, a small group of

people, or a single company. Case-studies involve measuring what is there and how it got there. In this sense, it is

historical. It can enable the researcher to explore, unravel and understand problems, issues and relationships. It

cannot, however, allow the researcher to generalise, that is, to argue that from one case-study the results, findings or

theory developed apply to other similar case-studies. The case looked at may be unique and, therefore not

representative of other instances. It is, of course, possible to look at several case-studies to represent certain

features of management that we are interested in studying. The case-study approach is often done to make practical

improvements. Contributions to general knowledge are incidental.

The case-study method has four steps:

1. Determine the present situation.

2. Gather background information about the past and key variables.

3. Test hypotheses. The background information collected will have been analysed for possible hypotheses. In

this step, specific evidence about each hypothesis can be gathered. This step aims to eliminate possibilities

which conflict with the evidence collected and to gain confidence for the important hypotheses. The

culmination of this step might be the development of an experimental design to test out more rigorously the

hypotheses developed, or it might be to take action to remedy the problem.

4. Take remedial action. The aim is to check that the hypotheses tested actually work out in practice. Some

action, correction or improvement is made and a re-check carried out on the situation to see what effect the

change has brought about.

The case-study enables rich information to be gathered from which potentially useful hypotheses can be generated. It

can be a time-consuming process. It is also inefficient in researching situations which are already well structured and

where the important variables have been identified. They lack utility when attempting to reach rigorous conclusions or

determining precise relationships between variables.

Diaries

A diary is a way of gathering information about the way individuals spend their time on professional activities. They

are not about records of engagements or personal journals of thought! Diaries can record either quantitative or

qualitative data, and in management research can provide information about work patterns and activities.

Advantages:

Useful for collecting information from employees.

Different writers compared and contrasted simultaneously.

Allows the researcher freedom to move from one organisation to another.

Researcher not personally involved.

Diaries can be used as a preliminary or basis for intensive interviewing.

Used as an alternative to direct observation or where resources are limited.

Disadvantages:

Subjects need to be clear about what they are being asked to do, why and what you plan to do with the data.

Diarists need to be of a certain educational level.

Some structure is necessary to give the diarist focus, for example, a list of headings.

Encouragement and reassurance are needed as completing a diary is time-consuming and can be irritating

after a while.

Progress needs checking from time-to-time.

Confidentiality is required as content may be critical.

Analyses problems, so you need to consider how responses will be coded before the subjects start filling in

diaries.

Critical incidents

The critical incident technique is an attempt to identify the more ‘noteworthy’ aspects of job behaviour and is based

on the assumption that jobs are composed of critical and non-critical tasks. For example, a critical task might be

defined as one that makes the difference between success and failure in carrying out important parts of the job. The

idea is to collect reports about what people do that is particularly effective in contributing to good performance. The

incidents are scaled in order of difficulty, frequency and importance to the job as a whole.

The technique scores over the use of diaries as it is centred on specific happenings and on what is judged as

effective behaviour. However, it is laborious and does not lend itself to objective quantification.

Portfolios

A measure of a manager’s ability may be expressed in terms of the number and duration of ‘issues’ or problems

being tackled at any one time. The compilation of problem portfolios is recording information about how each problem

arose, methods used to solve it, difficulties encountered, etc. This analysis also raises questions about the person’s

use of time. What proportion of time is occupied in checking; in handling problems given by others; on self-generated

problems; on ‘top-priority’ problems; on minor issues, etc? The main problem with this method and the use of diaries

is getting people to agree to record everything in sufficient detail for you to analyse. It is very time-consuming!

Sampling

Collecting data is time consuming and expensive, even for relatively small amounts of data. Hence, it is highly

unlikely that a complete population will be investigated. Because of the time and cost elements the amount of data

you collect will be limited and the number of people or organisations you contact will be small in number. You will,

therefore, have to take a sample and usually a small sample.

Sampling theory says a correctly taken sample of an appropriate size will yield results that can be applied to the

population as a whole. There is a lot in this statement but the two fundamental questions to ensure generalisation

are:

1.   How is a sample taken correctly?

2.   How big should the sample be?

The answer to the second question is ‘as large as possible given the circumstances’. It is like answering the question

‘How long is a piece of string’? It all depends on the circumstances.

Whilst we do not expect you to normally generalise your results and take a large sample, we do expect that you

follow a recognised sampling procedure, such that, if the sample was increased generalisation would be possible.

You therefore need to know some of the basics of sampling. This will be done by reference to the following example.

The theory of sampling is based on random samples – where all items in the population have the same chance of

being selected as sample units. Random samples can be drawn in a number of ways but are usually based on having

some information about population members. This information is usually in the form of an alphabetical list – called the

sampling frame.

Three types of random sample can be drawn – a simple random sample (SRS), a stratified sample and a systematic

sample.

Simple random sampling

Simple random sampling can be carried out in two ways – the lottery method and using random numbers.

The lottery method involves:

transferring each person’s name from the list and putting it on a piece of paper

the pieces of paper are placed in a container and thoroughly mixed

the required number are selected by someone without looking

the names selected are the simple random sample.

This is basically similar to a game of bingo or the national lottery. This procedure is easy to carry out especially if both

population and sample are small, but can be tedious and time consuming for large populations or large samples.

Alternatively random numbers can be used. Random numbers are strings of digits that have been generated by the

lottery method and can be found in books of statistical tables. An example of these is:

03

47

43

73

86

   

36

96

47

36

61

97

74

24

67

62

 

42

81

14

57

20

16

76

62

27

66

 

56

50

26

71

07

12

56

85

99

26

 

96

96

68

27

31

55

59

56

35

64

 

38

04

80

46

22

Random numbers tend to be written in pairs and blocks of 5 by 5 to make reading easy. However, care is needed

when reading these tables. The numbers can be read in any direction but they should be read as a singe string of

digits i.e. left to right as 0, 3, 4, 7 etc’, or top to bottom as 0, 9, 1, 1, 5, 3, 7, … etc. It is usual to read left to right.

The random number method involves:

Allocating a number to each person on the list (each number must consist of the same number of digits so

that the tables can be read consistently).

Find a starting point at random in the tables (close your eyes and point).

Read off the digits.

The names matching the numbers are the sample units.

For the example of selecting nine people at random from 90:

a)

The sampling frame is the list of 90 people. Number this list 00, 01, 02, …, 89. Note that each number has two digits

and the numbering starts from 00.

b)

Suppose a starting point is found at random from the random number tables and let this number be 16. Then the

person that has been numbered 16 is the first sample unit.

c)

Let the next two digits be 76, then the person numbered 76 is the second sample unit.

This procedure is repeated until the nine people have been identified.

d)

Any number occurring for second time is ignored as is any two-digit number over 89.

Simple random number sampling is used as the basis for many other sampling methods, but has two disadvantages:

1. A sampling frame is required. This may not be available, exist or be incomplete.

2. The procedure is unbiased but the sample may be biased. For instance, if the 90 people are a mixture of

men and women and all men were selected this would be a biased sample.

To overcome this problem a stratified sample can be taken. In this the population structure is reflected in the sample

structure, with respect to some criterion.

For example, suppose the 90 people consist of 30 men and 60 women. If gender is the criterion for stratification then:

30

of the sample should be men

90

ie.

30

x 9 = 3 men

90

60

of the sample should be women

90

ie.

60

x 9 = 6 women

90

Thus the sample reflects the population structure in terms of gender.

The three men and six women would then be selected by simple random sampling e.g., random numbers.

The problem with this approach is the criterion for stratification, (e.g., age, sex, job description), is chosen by you – it

is subjective and may not be the best or more appropriate criterion. Also a more detailed sampling frame is required.

Systematic sampling

Whilst not truly random this is a method that is used extensively because it is easy to operate and quick, even when

the population and the sample are large.

For example, for the population 90 and sample of nine:

Split the sampling frame in to nine equal groups.

i.e.

1 to 9

 

10 to 19

 

etc

 

80 to 89

Select a number between 1 and 9 using random number tables.

Suppose this number is 6.

Person numbered 6 is chosen.

Then the 16th, 26th, 36th, 46th, 56th, 66th, 76th, and 86th people are the remaining sample units.

If no sampling frame is available access to the population is necessary, such as customers of a business such as a

leisure centre, restaurant or museum.

Systematic sampling can be used by selecting a random number say 25.

Then the 25th person to enter is the first sample unit.

The 50th person to enter is the second sample unit.

This process is carried on until the required sample size is met.

This approach usually generates a good cross section of the population. However, you may need a team of people

when no sampling frame exists to help with counting, interviewing, etc.

Data recording and analysis

When you are at the planning stage of your research design, it is worth thinking about how you are going to record

your data and, even more importantly, how you are going to analyse it. It is pointless collecting data in a form that you

cannot understand or analyse! In the next two units, we help you with this. Make sure you check these issues out

before you carry out your primary data collection.

 

Some common worries amongst researchers are:

Will the research I’ve done stand up to outside scrutiny?

Will anyone believe my findings?

These questions are addressed by researchers by assessing the data collection method (the research instrument) for

its reliability and its validity.

Reliability

Reliability is the extent to which the same finding will be obtained if the research was repeated at another time by

another researcher. If the same finding can be obtained again, the instrument is consistent or reliable.

Validity

Validity is epitomised by the question: ‘Are we measuring what we think we are measuring?’ This is very difficult to

assess. The following questions are typical of those asked to assess validity issues:

Has the researcher gained full access to the knowledge and meanings of informants?

Would experienced researchers use the same questions or methods?

No procedure is perfectly reliable, but if a data collection procedure is unreliable then it is also invalid, but if it is

reliable then it is not necessarily valid.

Triangulation

Triangulation is crosschecking of data using multiple data sources or using two or more methods of data collection.

There are different types of triangulation, including:

time triangulation – longitudinal studies

methodological triangulation – same method at different times or different methods on same object of

study

investigator triangulation – uses more than one researcher.

Sampling error

Sampling error is a measure of the difference between the sample results and the population parameters being

measured. It can never be eliminated, but if random sampling is used, sampling error occurs by chance but is

reduced as the sample size increases. When non-random sampling is used this is not the case.

Basic questions we need to ask to assess a sample are:

Is the sample random and representative of the population?

Is the sample small or large?

Non-sampling error

All errors, other than sampling errors, are non-sampling errors and can never be eliminated. The many sources of

non-sampling errors include the following:

Researcher error – unclear definitions; reliability and validity issues; data analysis problems, for example,

missing data.

Interviewer error – general approach; personal interview techniques; recording responses.

Respondent error – inability to answer; unwilling; cheating; not available; low response rate.

Figure 3.1 summarises the relationship between the expected error and the sample size. You should note that there

is a law of diminishing return – to gain small additional accuracy the sample size has to be increased substantially.

Figure 3.1: Relationship between expected error and sample size

In this unit, we have covered the various methods used to collect data and the various methods of sampling and

assessing the data collection process. There is a lot to absorb and you need to make decisions about the best

methods to use to collect the data that you need to answer your research questions. Each piece of research is very

individual and when you come to writing up your methodology section you need to be able to justify and evaluate the

methods you have used. So it is a good idea to have planned this aspect very carefully!

 

This unit is designed to help you conduct an analysis of your data, use diagrammatic forms of

presentation and write the chapter of your dissertation called ‘Analysis and Discussion of

Findings’. We look at qualitative data analysis, quantitative data analysis, presentation of data

and writing up the results.

The purpose of analysing data is to obtain usable and useful information. The analysis, irrespective of whether the

data is qualitative or quantitative, may:

describe and summarise the data

identify relationships between variables

compare variables

identify the difference between variables

forecast outcomes.

Before we look at the various ways of analysing, presenting and discussing data, we need to clarify the differences

between qualitative research, quantitative research, qualitative data and quantitative data. Earlier, we distinguished

between qualitative research and quantitative research. It is highly unlikely that your research will be purely one or

the other – it will probably be a mixture of the two approaches. For instance, you may have taken a small sample

(normally associated with qualitative research) but then conducted a structured interview or used a questionnaire

(normally associated with quantitative research) to determine people’s attitudes to a particular phenomenon

(qualitative research). It is therefore likely that your ‘mixed’ approach will take a qualitative approach some of the time

and a quantitative approach at others. It depends on where you are in the research process.

A misconception, and source of confusion for many people, is the belief that qualitative research generates just

qualitative data (text, words, opinions, etc) and that quantitative research generates just quantitative data (numbers).

Sometimes this is the case, but both types of data can be generated by each approach. For instance, a postal

questionnaire or structured ‘interview (quantitative research) will often gather factual information, for example, age,

salary, length of service (quantitative data) – but may also seek opinions and attitudes (qualitative data).

A second misconception is that statistical techniques are only applicable for quantitative data. Once again, this is not

so. There are many statistical techniques that can be applied to qualitative data, such as ratings scales, that has

been generated by a quantitative research approach.

Unfortunately, many people are worried about numbers, and in particular about statistics, and everything that word

implies. Quantitative research and the analysis of quantitative data is consequently something to be avoided. But as

we have indicated above, this is rarely possible because qualitative data can also be analysed using statistics. An

understanding of basic statistical terms and ideas and the ability to carry out some statistical analysis (elementary or

otherwise) is essential for most researchers. Also competence in these techniques, even at a basic level, is a useful

skill in its own right.

A third misconception is that qualitative data analysis is easy. There are many ways of conducting qualitative

research and thus many ways of analysing the resulting (qualitative) data. For example, having conducted an

interview, transcription and organisation of data are the first stages of analysis. This would then be continued by

systematically analysing the transcripts, grouping together comments on similar themes and attempting to interpret

them and draw conclusions.

We deal with data that can be analysed statistically (quantitative data and some types of qualitative data) in the

section called quantitative data analysis. We cover data that cannot, or is very difficult, to analyse statistically in the

section called qualitative data analysis.

 

Qualitative data is subjective, rich, and in-depth information normally presented in the form of words. In

undergraduate dissertations, the most common form of qualitative data is derived from semi-structured or

unstructured interviews, although other sources can include observations, life histories and journals and documents

of all kinds including newspapers.

Qualitative data from interviews can be analysed for content (content analysis) or for the language used (discourse

analysis). Qualitative data is difficult to analyse and often opportunities to achieve high marks are lost because the

data is treated casually and without rigour. Here we concentrate on the content analysis of data from interviews.

Theory

When using a quantitative methodology, you are normally testing theory through the testing of a hypothesis. In

qualitative research, you are either exploring the application of a theory or model in a different context or are hoping

for a theory or a model to emerge from the data. In other words, although you may have some ideas about your topic,

you are also looking for ideas, concepts and attitudes often from experts or practitioners in the field.

Collecting and organising data

The means of collecting and recording data through interviews and the possible pitfalls are well documented

elsewhere but in terms of subsequent analysis, it is essential that you have a complete and accurate record of what

was said. Do not rely on your memory (it can be very selective!) and either tape record the conversation (preferably)

or take copious notes. If you are taking notes, write them up straight after the interview so that you can elaborate and

clarify. If you are using a tape recorder, transcribe the exact words onto paper.

However you record the data, you should end up with a hard copy of either exactly what was said (transcript of tape

recording) or nearly exactly what was said (comprehensive notes). It may be that parts of the interview are irrelevant

or are more in the nature of background material, in which case you need not put these into your transcript but do

make sure that they are indeed unnecessary. You should indicate omissions in the text with short statements.

You should transcribe exactly what is said, with grammatical errors and so on. It does not look very authentic if all

your respondents speak with perfect grammar and BBC English! You may also want to indicate other things that

happen such as laughter.

Each transcript or set of notes should be clearly marked with the name of the interviewee, the date and place and any

other relevant details and, where appropriate, cross-referenced to clearly labelled tapes. These transcripts and notes

are not normally required to be included in your dissertation but they should be available to show your supervisor and

the second marker if required.

You may wonder why you should go to all the bother of transcribing your audiotapes. It is certainly a time-consuming

business, although much easier if you can get access to a transcription machine that enables you to start and stop

the tape with your feet while carrying on typing. It is even easier if you have access to an audio-typist who will do this

labour intensive part for you. The advantage of having the interviews etc in hard copy is that you can refer to them

very quickly, make notes in the margins, re-organise them for analysis, make coding notations in the margins and so

on. It is much slower in the long run to have to continually listen to the tapes. You can read much faster than the tape

will play! It also has the advantage, especially if you do the transcription yourself, of ensuring that you are very

familiar with the material.

Content analysis

Analysis of qualitative data is not simple, and although it does not require complicated statistical techniques of

quantitative analysis, it is nonetheless difficult to handle the usually large amounts of data in a thorough, systematic

and relevant manner. Marshall and Rossman offer this graphic description:

"Data analysis is the process of bringing order, structure and meaning to the mass of collected data. It is a messy,

ambiguous, time-consuming, creative, and fascinating process. It does not proceed in a linear fashion; it is not neat.

Qualitative data analysis is a search for general statements about relationships among categories of data."

Marshall and Rossman, 1990:111

Hitchcock and Hughes take this one step further:

"…the ways in which the researcher moves from a description of what is the case to an explanation of why what is

the case is the case."

Hitchcock and Hughes 1995:295

Content analysis consists of reading and re-reading the transcripts looking for similarities and differences in order to

find themes and to develop categories. Having the full transcript is essential to make sure that you do not leave out

anything of importance by only selecting material that fits your own ideas. There are various ways that you can mark

the text:

Coding paragraphs – This is where you mark each paragraph with a topic/theme/category with an appropriate word

in the margin.

Highlighting paragraphs/sentences/phrases – This is where you use highlighter pens of different colours or

different coloured pens to mark bits about the different themes. Using the example above, you could mark the bits

relating to childcare and those relating to pay in a different colour, and so on. The use of coloured pens will help you

find the relevant bits you need when you are writing up.

With both the above methods you may find that your categories change and develop as you do the analysis. What is

important is that you can see that by analysing the text in such a way, you pick up all the references to a given topic

and don’t leave anything out. This increases the objectivity and reduces the risk of you only selecting bits that

conform to your own preconceptions.

You then need to arrange the data so that all the pieces on one theme are together. There are several ways of doing

this:

Cut and put in folders approach

Make several copies of each transcript (keeping the master safe) and cut up each one according to what is

being discussed (your themes or categories). Then sort them into folders, one for each category, so that you

have all together what each interviewee said about a given theme. You can then compare and look for

similarities/differences/conclusions etc. Do not forget to mark each slip of paper with the respondent’s name,

initials or some sort of code or you won’t be able to remember who said what. Several copies may be

needed in case one paragraph contains more than one theme or category. This is time consuming and

messy at first, but easier in the long run especially if you have a lot of data and categories.

Card index system

Each transcript must be marked with line numbers for cross-referencing purposes. You have a card for each

theme or category and cross-reference each card with each transcript so that you can find what everyone

has said about a certain topic. This is quicker initially but involves a lot of referring back to the original

transcripts when you write up your results and is usually only suitable for small amounts of data.

Computer analysis

If you have access to a computer package that analyses qualitative data (e.g. NUDIST) then you can use

this. These vary in the way they work but these are some of the basic common principles. You can upload

your transcripts created in a compatible word-processing package and then the software allows you to mark

different sections with various headings/themes. It will then sort all those sections marked with a particular

heading and print them off together. This is the electronic version of the folders approach! It is also possible

to use a word-processing package to cut and paste comments and to search for particular words.

There is a great danger of subjective interpretation. You must accurately reflect the views of the interviewees and be

thorough and methodical. You need to become familiar with your data. You may find this a daunting and stressful

task or you may really enjoy it – sometimes so much that you can delay getting down to the next stage which is

interpreting and writing up!

Presenting qualitative data in your dissertation

This would normally follow the topics, themes and categories that you have developed in the analysis and these, in

turn, are likely to have been themes that came out in the literature and may have formed the basis for your interview

questions. It is usually a mistake to go through each interviewee in turn and what they said on each topic. This is

cumbersome and does not give the scope to compare and contrast their ideas with the ideas of others.

Do not analyse the data on a question-by-question basis. You should summarise the key themes that emerge from

the data and may give selected quotes if these are particularly appropriate.

Note how a point is made and then illustrated with an appropriate quote. The quotes make the whole text much more

interesting and enjoyable to read but be wary of including too many. Please note also the reference to literature (this

one is an imaginary piece of literature) – you should evaluate your own findings in this way and refer to the literature

where appropriate. Remember the two concepts of presenting and discussing your findings. By presenting we mean

a factual description/summary of what you found. The discussion element is your interpretation of what these findings

mean and how they confirm or contradict what you wrote about in your literature section.

If you are trying to test a model then this will have been explored in your literature review and your methodology

section will explain how you intend to test it. Your methodology should include who was interviewed with a clear

rationale for your choices to explain how this fits into your research questions, how you ensured that the data was

unbiased and as accurate as possible, and how the data was analysed. If you have been able to present an adapted

model appropriate to your particular context then this should come towards the end of your findings section.

It may be desirable to put a small number of transcripts in the appendices but discuss this with your supervisor.

Remember you have to present accurately what was said and what you think it means.

In order to write up your methodology section, you are strongly recommended to do some reading in research

textbooks on interview techniques and the analysis of qualitative data. There are some suggested texts in the Further

Reading section at the end of this pack.

 

Here we are concerned with the basics of statistical analysis. However, we do not cover the techniques in detail but

provide a brief overview. If you are unsure of these or have forgotten them, you should refer to your notes from

previous studies or consult introductory statistics textbooks. We begin by looking at some basic ideas about analysis

and presentation of data. These are ‘variables’ and the related idea of ‘scales of measurement’.

Variables

Constant reference is made in statistics textbooks to the term variable. A variable is a characteristic of interest that

varies from one item to another and may take any one of a specified set of values or attributes. Variables are usually

classified as quantitative or qualitative. For example, consider a study of guests at a hotel. We may be interested in

the age of a guest, their spend and length of stay. Each characteristic is a quantitative variable because the data that

each generates is numerical – for instance, a guest may be 34 years of age, spend £500 and stay for seven days.

Quantitative variables generate quantitative data.

On the other hand, qualitative variables generate non-numerical or qualitative data. For instance, ‘nationality of hotel

guest’ is a qualitative variable because nationality can be classified as British, American, French, etc.

Scales of measurement

Many people are confused about what type of analysis to use on a set of data and the relevant forms of pictorial

presentation or data display. The decision is based on the scale of measurement of the data. These scales are

nominal, ordinal and numerical. (Strictly numerical can be sub-divided into interval and ratio – however, we do not

draw that distinction here.)

Nominal scale

A nominal scale is where:

the data can be classified into a non-numerical or named categories, and

the order in which these categories can be written or asked is arbitrary.

 

Ordinal scale

An ordinal scale is where:

the data can be classified into non-numerical or named categories

an inherent order exists among the response categories.

Ordinal scales are seen in questions that call for ratings of quality (for example, very good, good, fair, poor, very poor)

and agreement (for example, strongly agree, agree, disagree, strongly disagree).

Numerical scale

A numerical scale is:

where numbers represent the possible response categories

there is a natural ranking of the categories

zero on the scale has meaning

there is a quantifiable difference within categories and between consecutive categories.

Organising the data

Once you have collected the raw data, you need to organise it. This is a two-stage process:

1. The first step is to tabulate all the responses to each question for each respondent in a data sheet using the

coded values. It is advisable to construct this on a spreadsheet.

The data sheet for the questionnaire on restaurant staff attitude is given below.

How is this interpreted?

There were 40 respondents

Respondent 1 supplied the following data:

Question 1 (gender)

Response: 2 = female.

Question 2 (rating of manager)

Response: 2 = average.

Question 3 (attitude to work)

Response: 3 = OK.

Question 4 (salary)

Response: 2 = £8,000 - £12,000 pa.

Question 5 (age)

Response: 22 = 22 years of age.

2. The second step is to construct a summary sheet.

This summary sheet will be an amended version of the original question sheet (either questionnaire or interview

schedule) and contains:

a brief overview of the data collection process, including:

data collection method

sample size and sampling method

number of responses

geographical coverage

time frame for data collection

a count for each response alongside each question

the percentage equivalents.

To illustrate a summary sheet, a partially completed summary questionnaire is given below and refers to the

questionnaire on restaurant staff attitudes and the data on the data sheet.

Summary Questionnaire

Attitudes of Restaurant Workers

Based on 40 questionnaires returned from a random sample of 100 workers in 14 restaurants in the London Borough

of Ealing in February, 1999.

1.   Are you:

Male

19

47.5%

Female

21

52.5%

2.   Would you rate your manager as:

Good

11

27.5%

Average

14

35.0%

Poor

15

37.5%

At the top of this sheet, there is a statement that tells us how many questionnaires were returned, how many were

issued, the sampling method, when the data was collected and the geographical area that was surveyed.

A count has been made of the responses for Questions 1 and 2 and written opposite each response, together with

the percentage equivalents.

The advantages of the summary sheet are that it shows:

a summary statement of the data collection process

the exact wording of the questions

the order in which the questions were asked or presented

the number, and percentage, responding to each element of each question

 

So far you have collated the data and made some counts and determined percentages. The next step is to

summarise the data, if possible, with one or two summary statistics. Summary or descriptive statistics describe the

original data set (the set of responses for each question) by using just one or two numbers – typically an average and

a measure of dispersion.

You should remember the following points about summary statistics:

Mode is the most frequently occurring value, although it is not often used.

Median is the middle value.

Mean is found by adding the values and dividing by the number of values.

Quartiles (Q1 and Q3) are the 25% and 75% values respectively and are measures of dispersion about

the median.

Standard deviation is a measure of the dispersion about the mean; a small standard deviation implies the

data are tightly bunched about the mean, whereas a large standard deviation implies the data are widely

scattered about the mean.

Refer back to your statistics notes from previous studies to refresh your memory.

Different types of data (scales of measurement) can be summarised by different summary statistics. The table below

shows the types of averages and measures of dispersion for each type.

Data

Average

Dispersion

Nominal

Mode

 

Ordinal

Mode

 

 

Median

 

 

Mean

 

Numerical

Mode

 

 

Median

Quartiles

 

Mean

Standard deviation

Note that as the level gets higher more statistics can be determined.

With nominal data it is only possible to show the number or percentage of people or items falling within each

category. It is also possible to state which category includes the highest number of counts – the most popular

category or modal category.

If you think you require further practice on calculating the mean of a ratings scale, try the following activity.

Care is needed when comparing such a mean with another mean, because the data are ordinal and not numerical.

One question may give a weighted mean score of 2.1 and another question a weighted mean score of 4.2. It would

be incorrect to say the result for the first question is twice as good as the result for the second question. Remember

the weights are purely arbitrary. The data are not numerical and therefore the principle of ratios cannot be applied.

For numerical data, all three averages and their associated measures of dispersion can be determined. However, the

mode tends to be of little interest with this type of data and may be ignored in most situations. It may be necessary to

use a graphical technique such as a cumulative frequency curve (ogive) to determine the median and quartiles.

We can determine the mean and standard deviation using the formula:

The term in square brackets is the arithmetic mean. The approach to the calculation is to find the variance and then

take the square root to obtain the standard deviation.

For the data in question 4 in the summary questionnaire we have:

 

Annual salary

Number of respondents

Less than £8,000

6

£8,000 but less than £12,000

12

£12,000 but less than £16,000

10

£16,000 but less than £20,000

6

£20,000 but less than £24,000

4

£24,000 and above

2

This can be re-written with closed classes and the units in £000s to eliminate the zeroes as below. Three columns of

calculations are required as shown.

 

 

Freq.

Mid Pt.

 

 

 

f

x

fx

fx2

4 but less than 8

6

6

36

216

8 but less than 12

12

10

20

200

12 but less than 16

10

14

140

1,960

16 but less than 20

6

18

108

1,944

20 but less than 24

4

22

88

1,936

24 but less than 28

2

26

52

1,352

Total

40

 

544

8,608

 

Variance

=

 

=

215.2 - (13.6)2

 

=

215.2 - 184.96

 

=

30.24

St. dev.

=

÷30.24

 

=

5.5

The mean salary of respondents is £13,6000 per annum with a standard deviation of £5,500.

(The results have been multiplied by 1,000 to get the correct units for the data.)

To find the median and quartiles first determine the percentage cumulative frequencies and then draw an ogive

(cumulative frequency curve) and read off:

25% value to get the lower quartile Q1

50% value to get the median

75% value to get the upper quartile Q3.

 

f

cf

%cf

4 but less than 8

6

6

15

8 but less than 12

12

18

45

12 but less than 16

10

28

70

16 but less than 20

6

34

85

20 but less than 24

4

38

95

24 but less than 28

2

40

100

Total

40

 

 

The percentage cumulative frequencies are then plotted to correspond with the upper class limits. From the graph

(not drawn here) the following approximate results are obtained:

 

Q1

=

£8,700

Median

=

£12,800

Q3

=

£17,300

All the summary statistics determined so far have used the results as presented on the summary sheet. An

alternative approach is to use the raw data as presented on the data sheet. However, if you are going to use this

approach the data ideally should be on a spreadsheet where the in-built statistical functions can be used.

These functions are:

 

Summary statistic

Excel function

Arithmetic mean

Median

Mode

Standard deviation

Q1

Q3

=AVERAGE(cell range of data)

=MEDIAN(cell range of data)

=MODE(cell range of data)

=STDEVP(cell range of data)

=QUARTILE(cell range of data,1)

=QUARTILE(cell range of data,3)

So far the analysis has been concerned with determining some summary statistics. Analysis, however, consists of

more than this. In particular, analysis is concerned with establishing relationships between variables. There are two

common approaches to this, namely, cross-tabulations and correlation analysis.

Cross-tabulations

A cross tabulation is a matrix in which all categories representing one variable are presented in rows, and all

categories representing another variable are presented in columns. Although cross-tabulations can be constructed for

any type of data they are particularly useful for analysing nominal and ordinal data.

For instance, consider the questionnaire on the attitudes of restaurant staff, you may believe that a worker’s opinion

of their manager is dependent upon the gender of the respondent. This hypothesis may be investigated by

constructing a cross-tabulation for the two variables gender (Question 1) and opinion of manager (Question 2). The

blank table would look something like the following:

 

Gender (Q1)

Opinion of manager (Q2)

 

Good

(1)

Average

(2)

Poor

(3)

Total

Male (1)

 

 

 

 

Female (2)

 

 

 

 

Total

 

 

 

 

 

You would then count how many responses fall into each cell – this is called the cell frequency. Row totals, column

totals and a grand total are inserted as well. This is a time-consuming process and requires care, but invariably leads

to valuable information about the relationship between the two variables.

For this example and by referring to the data sheet, we can obtain the following completed cross-tabulation:

 

Gender (Q1)

Opinion of manager (Q2)

Total

 

Good

(1)

Average

(2)

Poor

(3)

 

Male (1)

8

8

3

19

Female (2)

3

6

12

21

Total

11

14

15

40

Cross-tabulations can be analysed on two levels:

1. Inspect the table to see if there are any patterns or cells with small and/or large cell frequencies. If there is,

make a statement to reflect this pattern or possible relationship. If there is no obvious pattern, with

frequencies being fairly even spread across the cells, then there is probably no relationship between the two

variables.

2. Test the independence of the two variables using a chi-square test. This is a sophisticated method and we

do not cover it here because of the required theoretical underpinning and complexity of the technique. If you

have not studied this technique before just use the method above.

If we consider the above table, it would appear that most males (16 out of 19) have a reasonable opinion of their

manager, whilst most females (12 out of 21) appear to have a poor opinion of their manager. This seems to indicate

that the opinion of manager is dependent on the gender of respondent (for this sample!), or, there is a relationship

between the two variables - gender and opinion of manager.

A possible pattern is less obvious but it would appear that males have a high rating of their work (13 out of 19 rating

1, 2 or 3), whereas females do not (16 out of 21 rating 3, 4 or 5). It would appear that the respondents’ rating of their

work is dependent on the gender of the respondent (for this sample).

The analysis could be continued by investigating the following hypotheses:

Is ‘rating of the manager’ dependent on ‘salary’?

Is ‘rating of the manager’ dependent on ‘age’?

Is ‘opinion of work’ dependent on salary’?

Is ‘opinion of work’ dependent on ‘age’?

Is ‘salary’ dependent on ‘age’?

It is possible to cross tabulate every question with every other question. This produces so much information that the

result is ‘information overload’ and you simply get very confused! You have to be selective about what you cross-

tabulate.

With cross-tabulations do not use percentages, only use the actual frequencies. This is because the calculation of a

percentage can be based on either row totals, or column totals, or the grand total. In other words, three percentages

are possible for each cell.

Correlation coefficient

This is another sophisticated technique that is commonly used to see if there is a linear relationship between two

variables. As with chi-square tests, you should only use this method if you have studied it previously.

 

Secondary data and the response counts or percentages associated with a question can be displayed in

diagrammatic forms such as a line graph, bar chart or pie chart. These can greatly enhance your findings and

subsequent discussion. If at all possible you should include some in your dissertation.

Whatever diagram you use, an associated commentary is essential. Do not leave it to the reader to work out what the

diagram shows. The commentary may:

state the obvious, such as the largest and/or the smallest, or the trend

highlight something that is not so obvious. This is preferable.

Whenever a diagram is used you should position the diagram as close as possible to the associated commentary in

the main body of the text and not in the appendix. Remember, the objective of using a diagram is to present

something that is fairly complicated in an easy-to-understand manner as the dissertation is read. Putting it in the

appendix at the back of the dissertation disrupts the flow of reading and understanding.

Two common and popular mistakes made by students when presenting data or findings are as follows:

1. The belief that every question or piece of data needs to have a diagram. This is not so. Be selective in the

type and number of diagrams used.

2. The use of a chart for simple data. For instance, a pie chart is often drawn for a question when there are just

two responses, such as a gender breakdown of respondents. This is simplistic and unnecessary.

Graphs and charts can be produced either within Word directly or by using ChartWizard in Excel and then importing

the chart into the document. These require substantial, but important, technical skills. Give yourself time to re-learn

them if you have forgotten them.

General conventions

If you do produce some diagrams, it is essential that you adhere to the following conventions:`

Line graphs

The numerical data are represented by a series of points, joined by a line, on a rectangular grid with two axes. A

single line is used for one set of data and multiple lines for more than one set of data.

 

Bar charts

Quantities are each represented by an individual bar or rectangle corresponding in length or height to the given value.

The main types of bar chart are:

Bar charts are inappropriate for large data sets with many bars and numerical data.

Pie charts

The percentage divisions of a whole quantity are represented by segments of a circle. The area of the complete circle

represents the total and is equivalent to 100%.

Pie charts are used to:

show the percentage parts of the whole; they are the circular version of a percentage component bar chart

highlight a particular component using an exploded or dynamic pie chart, where a slice of the pie is

extracted.

Pie charts should not be used when:

there are more than seven divisions to the data

there is more than one set of data; it can be done but it is difficult, as the radii of the circles have to be

proportional to the areas.

Guidelines

Histograms

Histograms are used to display quantitative data that have been grouped into classes. You should consult your notes

from previous studies on how to draw these.

We have seen that a lot of analysis can be undertaken with data that is produced from quantitative research. When

writing about this, do not give a question-by-question account of what you have discovered. Group the data into

themes or categories and use these as the basis for a logical structured discussion.

Do not quote too many percentages, especially in one paragraph.

Your discussion should be presented clearly and logically and should be relevant to your research questions,

hypotheses or objectives. Make sure that you relate your findings from the primary data collection and analysis to the

literature review. A good approach is to fit your findings to the structure of the literature review rather than trying to fit

the literature review findings to the analysis of the primary data.

You are looking for similarities and differences between the literature and your findings. If you think your findings

have confirmed some literature findings, say so and say why. Similarly, if you discover differences, say so and say

why.

 

This unit gives you the necessary information to write up your dissertation in the appropriate presentational style and

with the appropriate structure.

 

To view the Dissertation Style Docment, click on the button below.

To copy a Dissertation Style Template for MS Word, click on the button below.

 

The structure of the dissertation is in the following order:

Title page

Abstract

Acknowledgements

Contents page

Chapter 1: Introduction

Chapter 2: Literature Review

Chapter 3: Methodology

Chapter 4: Discussion of Analysis and Findings

Chapter 5: Conclusions

Bibliography

Appendices.

To view a document structured in the same way your dissertation should be structured, click on the button below.

The questions in the checklists that follow, identify what the markers are looking for and form the basis for the

marking criteria, which are given in the Module Study Guide.

Chapter 1: Introduction

Check-list: ask yourself the following questions:

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Is the overall style and presentation of the dissertation in accordance with that specified in the Module Study Guide?

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Is the title concise, coherent and appropriate?

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Is the abstract a concise (one page) summary of the main aims, methodology, findings and conclusions?

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Are acknowledgements made as appropriate?

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Is the contents page clear, concise and logically numbered? Are appendices, tables, illustrations and figures listed in

the contents page?

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Is the topic clearly stated and defined?

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Has background information been provided, if appropriate?

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Are all special and general terms defined?

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Has the dissertation been given a clear, overall purpose?

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Are the aims and objectives (or research questions) clear, relevant and coherent?

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Do aims, objectives, etc., go beyond mere description? Do they involve explanation, comparison, criticism or

evaluation?

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If a hypothesis is identified, is it a proper, testable hypothesis?

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Is the chapter clear, logical, readable and complete?

 

Chapter 2: Literature Review

Check-list: ask yourself the following questions:

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Has a comprehensive range of relevant literature been used? Is it pertinent to the research questions, or are you

giving the impression that almost everything you have read on or around the problem has been included with little

critical selection?

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Is the literature firmly rooted in a theoretical base? Has the literature of any related disciplines been included, if

appropriate?

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Are the sources used up-to-date, where appropriate, and do they have sufficient academic weight?

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Does the dissertation give evidence of a critical attitude towards source material? Does it compare, contrast and

criticise a number of relevant concepts/models/theories?

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Are the key themes and issues surrounding the research questions clearly drawn from the literature?

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Does it deal with relevant debates and controversies?

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Have sources been acknowledged and referenced fairly and properly? Is the bibliography at the end of the

dissertation complete and in the appropriate convention?

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Is the chapter clear, logical, readable and complete?

 

Chapter 3: Methodology

Check-list: ask yourself the following questions:

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Was the data collection method approved by your supervisor? For example, if you used an interview or questionnaire,

did the supervisor agree the questions prior to issue? If you have mentioned the university in any communication did

you get approval from the supervisor?

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Is there a clear rationale for methodology? Have you discussed the alternatives and have you discussed the

advantages and disadvantages of your chosen methods?

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Is the research methodology described fully so that it could be replicated by someone reading the dissertation?

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Are the research instruments (for example, blank questionnaires, interview questions, etc.,) included in the

appendices?

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Are the research instruments well designed with all questions etc., relevant to the research aims?

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Is the methodology described appropriate for the data required?

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Are sampling methods described in detail? Who are the respondents, how many are there and how were they

selected?

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Is generalisability (or otherwise) discussed?

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Are any constraints or limitations identified?

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Are data analysis methods discussed?

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Are reliability and validity issues addressed?

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Is there evidence of care and accuracy in the data collection process?

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Has the methodology been evaluated in retrospect, with suggestions for improvement if the research were to be

undertaken again?

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Is the chapter clear, logical, readable and complete?

 

Chapter 4: Analysis and Discussion of Findings

Check-list: ask yourself the following questions:

Generally:

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Is all data presented relevant to the research question(s), aims and objectives or hypotheses?

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Have you identified patterns in the data?

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Are the analysis methods used appropriate to the data collected?

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Is the analysis thorough and complete?

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Have a reasonable number of diagrams been included if appropriate?

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Are all appendices referred to in the text?

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Are the findings presented clearly and interestingly for the reader to follow? Are the key themes and issues

discussed, with useful tables and charts embedded in the text and with the appendices being used appropriately for

bulky and/or less interesting/essential data?

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Are all statements made supported by the data?

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Have the findings of the primary research been compared and contrasted with findings/theories/models/concepts

derived from the literature review?

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Does the discussion deal with relevant debates and controversies?

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Is the chapter clear, logical, readable and complete?

 

In addition:

For questionnaires:

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Do the appendices contain a data sheet, a summary questionnaire and details of statistical analysis undertaken?

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Have summary statistics been calculated?

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Does any statistical analysis make the most of the data collected?

 

For interviews:

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Do the appendices contain data collected and analysed, such as interview transcripts?

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Is the analysis methodical and thorough?

 

For observations:

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Do the appendices contain back-up data on observations carried out, such as data recording sheets?

 

For other methods:

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Is any qualitative analysis methodical and thorough?

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Is the most made of the data collected?

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Is any statistical analysis possible to make the most of the data collected?

 

Chapter 5: Conclusions

Check-list: ask yourself the following questions:

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Do the conclusions follow on from the findings? Are the conclusions well grounded in the evidence and arguments

presented? Are any contentious conclusions backed up by reasoned arguments and evidence?

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Are the conclusions discussed in context? Are they applicable to a wider scenario?

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Is the chapter clear, logical, readable and complete?

 

Final check-list: ask yourself the following questions:

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Does the dissertation have an overall coherence?

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Has the dissertation been spell- and grammar-checked?

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Has the dissertation got a word count?

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Is each page numbered?

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Have you read it from start to finish?

The final finally

The list below shows the last acts of undertaking a dissertation. Do not leave these to the hour before the hand-in

deadline. They take a considerable amount of time. Remember there will probably be many other students handing in

at the same time, so you will probably find queues for binding, photocopiers, etc.

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Make a back-up copy of the disk.

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Print the dissertation if you have made any changes during the final read through.

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Make as many paper copies as you need.

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Have the two copies that are to be handed in bound.

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If you want your own copies bound, have these bound too.

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Fill in two cover sheets (one for each copy) correctly.

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Hand the two copies in before the deadline.

Celebrate!