Applied Quantitative MethodsMBA course Montenegro

Peter BaloghPhD

baloghp@agr.unideb.hu

• BASIC DATA OF THE SUBJECT• • Name of the subject: Applied Quantitative Methods• Course status: obligatory• Language: English• Subject educator Name: Dr. Peter Balogh• Title: Associate Professor• Affiliation: University Debrecen• Period: September 2011• • Prerequisite: none• • Objective of the training: The students became familiar with the use of

quantitative methods in business• • Contact education: 20 hours• Consultation: 0 hours• Individual assignment: 85 hours• Total: 105 hours• Credit: ECTS : 8

• Description of the individual assignment: – Prepare and present a case study using the quantitative methods

within a working group.• • Examinations requirements: • Oral: Presentation• Written: Prepare a case study using the quantitative methods• • Compulsory literature:• Jon Curwin and Roger Slater: Quantitative Methods for Business

Decisions, Fifth edition, • Cengage Learning Business Press, ISBN-13: 978-1861525314• • Recommended literature:• David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffry

D. Camm, Kipp Martin: Quantitative Methods for Business, Cengage Learning Business Press, (2010) ISBN-13: 978-0-324-65175-1

Course Design

• Part lecture, part skills development– Usually one major topic per day– Some time devoted to working with statistical

software packages (excel and SPSS)

Course Reading

Jon Curwin and Roger Slater: Quantitative Methods for

Business Decisions

Statistical Software

• All course examples will use EXCEL

• You can download the excel files of the course book:

http://www.agr.unideb.hu/~baloghp/Montenegro

Software and ComputersBring your laptop to class if

applicable.

We will devote class time in many sessions to working with statistical software.

I encourage you to sit with anyone who knows the MS EXCEL software package when we begin to use it in class.

Overall Course Goals

• You will have good knowledge of common research methods used in quantitative research (surveys, experiments)

• You will understand basic univariate statistics, bivariate statistics, linear regression and time series analysis

• You will be able to use the MS EXCEL to conduct statistical analyses

Description of the contact education I.

• Hour 1-4: Quantitative information• The quantitative approach• Managing data• Survey methods• Presentation of data• Hour 5-8: Descriptive statistics• Measures of location• Measures of dispersion• Index numbers

Description of the contact education II.

• Hour 9-11: Measuring uncertainty• Probability• Discrete probability distributions• The normal distribution

•Statistical inference• Confidence intervals• Significance testing• Non-parametric tests

Description of the contact education III.• Hour 12-15: Relating variables and predicting

outcomes• Correlation• Regression• Multiple regression and correlation• Time series

1. The quantitative approach

• Quantitative information:• We can get data quickly, but we need to be sure

that we are working on the right problem and that the data is valid.

• Data means– a few recording– an extensive national or international survey

• An item of data becomes information when it informs the user.

1. The quantitative approach

• Quantitative information:• Internet has transformed the flow and

availability of data.• The ability to manage data, produce information

and work with problems are all seen as and important business competencies.

1. The quantitative approach

• Quantitative information:• Desk research:– First you need checking what work has already been

done.– Provide information or identify techniques.– It is always helpful to find a questionnaire that has

been used previous study and may only require some modification.

1. The quantitative approach

• Quantitative information:• Managing numbers is an important part of

understanding and solving problems.• The collecting together of numbers, and other

facts and opinions provides data.• This data only becomes information when it

informs the user!!• The quantitative approach is more than just

‘doing sums’.• It is about making sense of numbers within a

context.

1. The quantitative approach

• 1.1 Problem solving• 1.2 Methodology• 1.3 Models• 1.4 Measurement• 1.5 Scoring models

1.1 Problem solving

• To understand problems within a context, it can be useful to work through a number of stages:

• defining (and redefining) the problem, • searching for information,• problem description (and again redefinition if

necessary),• idea generation,• solution finding and finaly,• acceptance and implementation.

Problem solving

what we have and what we want!!!

1.2 Methodology• Old methods New methods• Reliability and validity of findings (conclusions)• Was the purpose of the research clear?• Was this research necessary? (desk research)• Was the means of data collection appropriate?• What can we infer?

(-inductive approach generalization-deductive approach)

1.3 Models

• 1.3.1 Model abstraction• 1.3.2 The development of a mathematical

model• 1.3.3 Models of uncertainty• 1.3.4 Computer-based modelling

Modelling

Inputs Transformation process

Assumptions

Outcomes

1.3 Models

• A model is a representation of real objects or situations– A good understanding of the object or situation– The recognition of all relevant variables– The understanding of relationships– The ability to undertake analysis

1.3.1 Model abstraction

• Physical (or iconic)• Schematic

(organization charts, flowcharts)• Analogue

(colours on a map: water, forest)• Symbolic (or mathematical)

(numbers, letters, special characters, symbols)

Least abstract

Most abstract

1.3.2 The development of a mathematical model

• A variable is a quantity or characteristic of interest that is allowed to change within a particular problem (students’ mathematics mark, travel time)

• A parameter is fixed for a particular problem.• An assumption is something we accept to be

true for the model we are working on.

1.3.3 Models of uncertainty

• Deterministic Stochastic (Probabilistic)

• Expected value Mean

1.3.4 Computer-based modelling• Computational

(spreadsheets, ‘what if’)• Analytical

(mathematical techniques and manipulation)

• Simulation(equations and distributions)

• Expert systems(advising on solution)

Least abstract

Most abstract

1.4 Measurement• Measurement is about assigning a value or a score

to an observation.• Measurement is the representation of – type,– size or – quantity by numbers.

• How we work with data will depend on the level of measurement achieved.

• Measurement can be categorized as:nominal, ordinal, interval, ratio

1.4 Measurement• Nominal (or categorical) level of measurement:• If responses merely classified into a number of

distinct categories, where no order or value.• The classification of survey respondents on the

basis of – religious affinity, – voting behaviour or – car ownership.

• The numbers assigned give no measure of amount or importance.

1.4 Measurement• Nominal (or categorical) level of measurement:• For data processing convenience, we may code

respondents 0 or 1 (e.g. YES or NO) or 1, 2, 3 (Party X, Party Y, Party Z), but these numbers do not relate to meaningful origin or to a meaningful distance.

• We cannot calculate statistics (mean, standard deviation).

• We can make percentage comparisons (e.g. 30 % will vote for party X), present data using bar charts or use more statistical methods (non-parametric tests).

1.4 Measurement• Ordinal level of measurement:• has been achieved when it is possible to rank order

all categories according to some criteria.• The preferences indicated on a rating scale ranging

from ‘strongly agree’ to ‘strongly disagree’ or the classification of respondents by social class (occupational groupings A, B, C1, C2, D, E) are both common examples where ranking is implied.

• Individuals are often ranked as a result of performance in sporting events or business appraisal.

1.4 Measurement• Ordinal level of measurement:• In these examples we can position a response or a

respondent but cannot give weight to numerical differences.

• It is as meaningful to code a five point rating scale 7, 8, 12, 17, 21 as 1, 2, 3, 4, 5 though the latter is generally expected.

• Only statistics based on order really apply.

1.4 Measurement• Ordinal level of measurement:• You will, however, find in market research and

other business applications that the obvious codings are made (e.g. 1 to 5) and then a host of computer-derived statistics calculated.

• Many of these statistics can be useful for descriptive purposes, but you must always be sure about the type of measurement achieved and its statistical limitations.

!

1.4 Measurement• Interval scale:• is an ordered scale where the differences between

numerical values are meaningful.• Temperature is a classic example of an interval scale, the

increase on the centigrade scale between 30 and 40 is the same as the increase between 70 and 80.

• However, the heat cannot be measured in absolute terms (0 oC does not mean no heat) and it is not possible to say that 40 oC is twice as hot as 20 oC, but we can say it is hotter.

• In practice there are few business-related measurements where the subtlety of the interval scale is of consequence.

1.4 Measurement• Ratio scale:• The highest level of measurement,

- which has all the distance properties of the interval scale and in addition,- zero represents the abscence of the caracteristic being measured.

• Distance and time are good examples.• It is meaningful, for example, to refer to 0 time and 0

distance and refer to one journey taking twice as long as another journey or one distance as being twice as long as another distance.

1.4 Measurement

1.4 Measurement• In summary, it is considered more powerful to

achieve measurement at higher level as this will contain more discriminating information;

• it is more useful to know how many cigarettes a respondent smokes on average (0 or more) than just whether they smoke or not.

• The measurement sought will depend on the purpose of the research.

1.4 Measurement• Another useful system of classification is whether

measurement is discrete or continuous.• Measurement is discrete if the numerical value is

the consequence of counting. (the number of respondets, the number of companies)

• Continuous measurement can take any value within a continuum, limited only by the precision of the measurement instrument. (5 seconds or 5.17 seconds)

Quantitative and Qualitative Perspectives

• "There's no such thing as qualitative data. Everything is either 1 or 0“ – Fred Kerlinger

• "All research ultimately has a qualitative grounding“– Donald Campbell

Quantitative and Qualitative Perspectives• First it is useful to distinguish between the quantitative

and qualitative approaches to problem solving.• Essentially, the quantitative approach will describe and

resolve problems using numbers.• Emphasis will be given to:– the collection of numerical data,– the summary of that data and– the drawing of conclusions from data.

• Measurement is seen as important and factors that cannot be easily measured, such as attitudes and perceptions, are generally difficult to include in the analysis.

Quantitative and Qualitative Perspectives• Qualitative approaches describe the behaviour of

people individually, in groups or in organisations.• Description is difficult in numerical terms and is likely to

use illustrative examples, generalization and case studies.

• The qualitative approach can use a variety of methods such as observation and the written response to unstructured questions.

• Data may come in the form of script, for example, transcripts of interviews or observations such as video recordings.

1.5 Scoring models

• Scoring models provide a way of combining such information and informing decision-making.– Can provide a useful basis for thinking about the

problem

2. Managing data

„The truth is out there somewhere”

2.1 Issues of data collection

• The five W’s and H technique:– Who?, What?, Where?, When?, Why? and How?

• Who? is an important question in any problem. Data will always relate to a particular group of people or set of items in time and we use this concept to define the population we will be working.

• The population is defined as those people or items of interest.– Given limited resources, including time, the identification

of the relevant population is essential. Women Man

2.1 Issues of data collection (cont.)

• Having decided who, we must then consider whether we need information on all of them or just a selection.

• A census is a complete enumeration of all those people or items of interest (whereas a sample is just a selection from all those people or items).

2.1 Issues of data collection (cont.)• What? data will depend on the purpose of the

research.• A statistical enquiry may require the collection of

new data, referred to as primary data, or be able to use existing data, referred to as secondary data. (Combination of both sources.)

• Sources of primary data include observation, group discussions and the use of questionnaires. Collection for a specific project. – Take a long time to collect,– Be expensive

2.1 Issues of data collection (cont.)

• Secondary data has been collected for some other purpose.

• Low cost but may be inadequate for purposes of the inquiry.

• Example: The impact of a new shopping center on the local community!!

• First step Second step

2.1 Issues of data collection (cont.)• Where? to find the right kind of data when you need it or where

to find the people of interest when you need them is an important skill.

• In organizational research it is often useful to distinguish between internal and externally generated data.

Recent sales volume, sales value, number of employees, expenditure on advertising, expenditure on research

The data generated by national governments, local governments, chambers of commerce, Internet

You still need to question its validity and reliability.This stage of searching for data is often referred to desk research.

2.1 Issues of data collection (cont.)

• Why? is seen as part of a questioning approach that should lead to greater clarification and a justification of approach. Useful technique called the why technique .

• Why did you say that? • Why should that be the case?• Why use that data?

2.1 Issues of data collection (cont.)• Chapter 2 and 3 are particularly concerned with the

how? • Having defined the population of interest and the

purpose of the research, a number of issues will need to be addressed:– Whether existing published sources provide sufficient

information– Whether useful information can be found through an

Internet search– What type of sampling should be used, if any– How data should be collected– How questions should be designed, if required

2.2 Published sources

Office for National Statistics (ONS)• The Annual Abstract of Statistics• The Monthly Digest of Statistics• Financial Statistics• Economic Trends The Economic and

Labour Market Review• Social Trends

• The most comprehensive source of statistics in the UK, Annual Abstract of Statistics is a statistical encyclopaedia including over 10,000 series of data and covering key aspects of the UK’s economic, social and industrial life.

• It covers the following areas: parliamentary elections; international development; defence; population and vital statistics; education; labour market; personal income, expenditure and wealth; health; social protection; crime and justice; lifestyles; environment, housing; transport and communications; national accounts; prices; government finance; external trade and investment; research and development; agriculture, fisheries and food; production; banking and insurance and service industry.

• Monthly Digest of Statistics (MDS) provides the latest monthly and quarterly statistics for UK businesses, economy and society. An important reference work, it is an indispensable source of statistics containing twenty chapters of tables updated each month.

• Did you know…?• In 2007 the average hourly earning (excluding overtime)

for men was £14.98 but for women it was £12.40.• February 2008 was the sunniest since 1929 for England,

Wales and the UK as a whole. But in NW Scotland some weather stations recorded over 200 percent average rainfall.

• Wind farms supplied 3.79 terawatt hours of electricity in 2007, the equivalent of 0.33 million tonnes of oil.

• The most popular destination of air passengers departing from the UK between April and June 2008 was Spain at over 8 million, followed by the USA at almost 5 million.

• Almost half of adult internet users in the UK use internet banking (49 per cent), although the most popular use for the internet is for sending and receiving e-mails (97 per cent).

• Financial Statistics is a monetary compendium of the UK's key financial and monetary statistics. Published monthly, it contains data on public sector finance, central government revenue and expenditure, money supply and credit, banks and building societies, interest and exchange rates, financial accounts, capital issues, balance sheets and balance of payments.

Publication title: Economic Trends (discontinued)This monthly compendium of statistics and articles on the UK economy was been

replaced by the Economic and Labour Market Review.

• Economic & Labour Market Review (ELMR) provides an up-to-date summary of the UK economy and labour market, bringing statistics to life through news, reviews and features that highlight the most recent trends and developments through impartial commentary and analysis.

• ELMR provides readers with new analysis of major economic measures including output, expenditure, prices, income and welfare, employment and pay.

• The journal is an authority on how economic measurement responds to a changing economy and to new policy challenges, publishing the latest-thinking on how economists and statisticians are helping to shape international standards.

• ELMR assesses the impact of new statistical methodologies and highlights the benefits to users of newly released or improved official statistics. The journal brings together a broad range of statistics, commentary and analysis from which users can draw a comprehensive picture of the UK economy and labour market.

• An established reference source, Social Trends draws together the most up-to-date social and economic data from a wide range of government departments and other organisations. Data is presented clearly in a combination of tables, figures and text providing the ideal tool for researching life and lifestyles in the UK.

• Each chapter focuses on a different social policy area: population, households and families, education and training, labour market, income and wealth, expenditure, health, social protection, crime and justice, housing, environment, transport, lifestyles and social participation.

European Statistical Sources1. Non-governmental sources:– Mintel Market Intelligence Report (monthly

reports on consumer products)– Retail Business– Marketing in Europe– Kompass Directory (provides information on a

variety of companies)– NEILSEN reports on markets and shopping

behaviour– ADMAP (Warc's monthly magazine)

2. European Official Statistics

– ADMAP (Warc's monthly magazine)Warc is home to thousands of effectiveness case studies from across the world charting the success strategies of winning brands in every sector and market.

„Extremely relevant articles by great practitioners in an easy to assimilate format - just what the overstretched marketer needs"Michael Harvey, Global Head of Planning, DiageoDiageo is the world's leading premium drinks business with an outstanding collection of beverage alcohol brands across spirits, beer and wine. These brands include Johnnie Walker, Crown Royal, J&B, Windsor, Buchanan's and Bushmills whiskies, Smirnoff, Ciroc and Ketel One vodkas, Baileys, Captain Morgan, Jose Cuervo, Tanqueray and Guinness.

European Official Statistics• Europe in figures - Eurostat yearbook 2010 • Basic figures on the EU• European Business: Facts and figures - 2009 editi

on • Key figures on European business - with a special

feature on SMEs • Key figures on Europe - 2011 edition • Forestry in the EU and the world • Science, technology and innovation in Europe • Food: from farm to fork statistics

• Europe in figures – Eurostat yearbook 2010 – presents a comprehensive selection of statistical data on Europe. With just over 450 statistical tables, graphs and maps, the yearbook is a definitive collection of statistical information on the European Union. Most data cover the period 1998-2008 for the European Union and its Member States, while some indicators are provided for other countries, such as candidate countries to the European Union, members of EFTA, Japan or the United States. The yearbook treats the following areas: the economy; population; health; education; the labour market; living conditions and welfare; industry and services; agriculture, forestry and fisheries; trade; transport; environment and energy; science and technology; and Europe’s regions. This edition’s spotlight chapter covers national accounts statistics – with a particular focus on the economic downturn observed during 2008/2009.

• The quarterly series “Basic figures on the EU” presents the freshest Eurostat data on a small number of key indicators in the economic and social fields. Each issue is released during the second month of each quarter.

• This publication gives a comprehensive picture of the structure, development and characteristics of European business and its different activities: from energy and the extractive industries to communications, information services and media. It presents the latest available statistics from a wide selection of statistical sources describing for each activity: production and employment; country specialisation and regional distribution; productivity and profitability; the importance of small and medium sized enterprises (SMEs); work-force characteristics; external trade etc.

This publication summarises the main features of European business and its different activities in a concise and simple manner. The publication is intended to function as a showcase for and introduction to the data available in this field. This edition includes a special feature section on SMEs, which presents an analysis of the different characteristics of micro, small, medium and large enterprises

• Key figures on Europe presents a selection of statistical data on Europe. Most data cover the European Union and its Member States, while some indicators are provided for other countries, such as members of EFTA, candidate countries to the European Union, Japan or the United States. The pocketbook treats the following areas: economy and finance; population; health; education and training; the labour market; living conditions and social protection; industry, trade and services; agriculture, forestry and fisheries; international trade; transport; the environment; energy; and science and technology.

• The International Year of Forests 2011 is a UN initiative reinforcing the message that forests are vital to the survival and well-being of mankind. This Eurostat publication supports the UN initiative by statistically depicting forests in their various dimensions.

• This publication presents information for the EU and its Member States, as well as comparisons with countries that have considerable forest resources.

• This publication draws a comprehensive picture of the Science, Technology and Innovation activities in the European Union as carried out by its people, enterprises and governments. It provides the reader with statistical information to appreciate the evolution and composition of science and technology in Europe and its position with regard to its partners. The pocketbook is divided into seven chapters among which: Government budget appropriations or outlays on Research and Development (GBAORD), R&D Expenditure, R&D Personnel, Human Resources in Science and Technology, Innovation, Patents, High-technology.

• This pocketbook provides the reader with information on how the food chain evolves in Europe; it presents a range of statistical indicators for each step of this chain from the farm to the fork, passing from production on the farm, through food processing, to logistical activities such as importing, transporting and distributing, before reaching the end consumer either through purchases made in retail outlets or through the consumption of food and drink in cafés, bars and restaurants.

• Secondary data will often provide a useful overall description (e.g. economic or social trend) and inform the collection of primary data.

• Primary data will add specific detail, particularly current attitudes and opinions.

2.3 Internet sources• Office for National Statistics (ONS)http://www.statistics.gov.uk/hub/index.html

http://www.ons.gov.uk/ons/index.html• Surveys:http://www.ons.gov.uk/ons/guide-method/surveys/list-of-surveys/

index.html• http://www.roughguides.com/• www.dis.strath.ac.uk/business/• General Global Marketing Informations:http://webpages.dcu.ie/~gannonm/Websites%20General%20Global

%20Marketing%20Information.htmlEUROSTAT:http://epp.eurostat.ec.europa.eu/portal/page/portal/eurostat/home

• Essentially, we need to be able to evaluate such information, and be ready to reject any that is suspect

• To check that data from the web is – appropriate– complete– without bias

• Big advantage of the Internet:– the scale of the information, which cannot be

matched by any imaginable traditional library

• Disadvantage:– the lack of any quality control

2.4 A census or a survey?• We need to decide whether to include– all people (item) undertake a census– or take a selection sample

• Census:– Representative! Mean, Standard Deviation– prohibitively expensive,– prohibitively time consuming,– limit the possible depth of the enquiry

• Designed survey can provide – the acceptable quality of results – at lower costs and– greater speed

2.4 A census or a survey?

• A census will attempt to include everyone• providing maximum numbers for analysis• avoiding conserns about sampling or selection

bias• Provide a benchmark for research activities

(age, gender, ethnic origin, …..)

• Population census

2.4 A census or a survey?• Full censuses have taken place in the United

Kingdom every ten years since 1801 with the exceptions of 1941 (during the Second World War).

• In addition to providing a wealth of interesting information about aspects of the make-up of the country, the results of the census play an important part in the calculation of resource allocation to regional and local service providers, by governments in the United Kingdom and European Union levels.

• The last: 27 March 2011• The next census in United Kingdom will take place in

March 2021

2.4 A census or a survey?

• The term ‘census’ is usually associated with a government count of the population, but a census can be any complete count

• An identified population is small• Local or sub-group level• A census can be taken of – all the suppliers to a particular company– all the schools in the UK – all the sports shops in Leeds

2.4 A census or a survey?

• A survey is likely to be preferred when:– it is known as a methodology that works– cost constraints exit– time constraints exit

• Most commercial and most governmental research will based on survey methodology

• If the selected sample is representative and sufficiently large, then the results will be good enough for purpose.

2.4 A census or a survey?• The procedure used to select the sample is particularly

important and this is described by the sample design. The sample needs to represent the population in such a way that results from the survey can be used to make generalizations about the population. We talk about making an inference from the sample to the population.

• The concepts of inclusion and exclusion are also important in sample design.

• General election result – If you were to ask the next five (10, 100) people you see

how they are likely to vote at the next general election, it is very unlikely that the answers given would be a guide to general election result.

2.4. 1 How should we decide sample size?

• The size of the sample required will depend on the following factors:– the accuracy required– the variability of the population– the detailed required in analysis

2.4.1 How should we decide sample size?

• If an accuracy of ± 1 % is required rather than ±5% for example, then a larger sample will be necessary.

• If the average weekly household expenditure on a particular item is only required to an accuracy of ±£5.00 rather than ±£0.50 then a smaller sample should be sufficient.

• The important point here is that the user or client needs to be able to specify such levels of accuracy.

2.4. 1 How should we decide sample size?

• The variability of the population will also be a determining factor in the sample size required.

• In the extreme case where everyone held exactly the same opinion (no variability existed) we would only need to ask one person to make an inference to the population as a whole.

2.4. 1 How should we decide sample size?

• As views become variable, larger samples are required.

• If accuracy is also required by subgroup, e.g. female smokers under 25 years of age, then we would need to ensure that the sample was sufficiently large to provide the necessary number in each of the subgroups.

2.4. 1 How should we decide sample size?

• Since most surveys are not designed to find out a single piece of information, but the answers to a whole range of questions, the determination of sample size can become extremely complex.

• It has been found that samples of about 1000 give results that are acceptable when sampling the general population.

2.4. 1 How should we decide sample size?

• 'Gallup and other major organizations use sample sizes of between 1000 and 1500 because they provide a solid balance of accuracy against the increased economic cost of larger and larger samples.

• If Gallup were to - quite expensively - use a sample of 4000 randomly selected adults each time it did its poll, the increase in accuracy over and beyond a well-done sample of 1000 would be minimal, and generally speaking, would not justify the increase in cost.‘

Source: www.gallup.com

2.5 Market research • Market research is seen as a major industry. • Data is collected on behalf of a range of organizations,

much of it for business use. • Data can have considerable commercial value and

access can be limited. • A variety of methods are used to collect data including

face-to-face interviewing, telephone interviewing, and group discussions.

• Market research provides information on people’s preferences, attitudes, likes and dislikes, and can help companies understand what consumers want.

• National and local government use market research to provide the data to inform policies on everything from planning local transport to the provision of efficient health and social services.

2.5 Market research • Market research can be directly concerned with a market

(which will need definition) and can provide information on market size, market trends, market share by brand, customer characteristics and other factors.

• Aspects of market research include advertising and promotional research, product research and distribution.

• Market research companies also sell a range of services, and will frequently undertake research for government, both national and local, academic projects and not-for-profit organizations.

• The Market Research Society provide a range of useful information on their website: http://www.mrs.org.uk

2.5 Market research

2.6 Conclusion• Obtaining and using data as information is an

important part of understanding and solving any problem.

• There is little doubt about the volume of data now available, and any search of the Internet can easily produce reams of computer print out.

• As with all problem solving we need to work within boundaries that ensure the problem remains manageable and yet does not exclude new avenues of enquiry.

• Given the diversity of possible data sources we need to check that data is appropriate, adequate and without bias.

2.6 Conclusion• As discussed, the choice is rarely between

secondary data (existing data) or primary data (new data that needs to be collected for the specific purpose).

• Secondary data will help describe and define the existing problem.

• The examination of secondary data can also provide guidance on what research methods work and which don't.

• Primary data will generally be needed to add specific detail.

2.6 Conclusion• The purpose of any statistical investigation needs to be

clear. • A statement that we wish to investigate the

management of change within the organization will mean different things to different people.

• In this case, we need to be clear about our meaning of change or changes, 'management' and the general context.

• Decisions will need to be made on who to include and who to exclude.

• In all statistical work the definition of population (all those people or items of interest) is particularly important.

• If we refer to the workforce, for example, do we mean only full-time employees, those at a particular location or those doing a particular job?

2.6 Conclusion• It is a frequently reported experience that

'desk research' yields some of the information required but also yields other data of interest and a wealth of new ideas.

• It is also worth considering how much research is genuinely original!

• If the purpose of the statistical investigation requires the collection of original data, then the sample survey is probably the most widely used method in business and economics.

2.6 Conclusion• Once collected, data needs to be collated and

presented (see Chapter 4). • Available computer hardware and software now

allows data to be stored, manipulated and analysed with relative ease.

• Many types of computer software are available for dealing with survey data.

• You could use a standard spreadsheet, such as, Excel or Lotus-123 to record the answers (in a coded form), or you could use more specialized software such as SPSS.

• The choice that you make will depend on the size of the survey, the resources available and the sophistication of the analysis necessary.