CHAPTER 1: MEANING AND CHARACTERISTICS OF RESEARCH

  Meaning of ResearchResearch is defined as the scientific investigation of phenomena which includes collection, presentation, analysis and interpretation of facts that lines an individual’s speculation with reality.

  Characteristics of Research1.      Empirical. Research is based on direct experience or observation by the

researcher.2.      Logical. Research is based on valid procedures and principles.3.      Cyclical. Research is a cyclical process because it starts with a problem and

ends with a problem.4.      Analytical. Research utilizes proven analytical procedures in gathering the

data, whether historical, descriptive, experimental and case study.5.      Critical. Research exhibits careful and precise judgment.6.      Methodical. Research is conducted in a methodical manner without bias

using systematic method and procedures.7.      Replicability. The research design and procedures are replicated or repeated

to enable the researcher to arrive at valid and conclusive results.  Qualities of a Good Researcher1.      Research-oriented2.      Efficient3.      Scientific4.      Effective5.      Active6.      Resourceful7.      Creative8.      Honest9.      Economical10.  Religious  Characteristics of the Researcher1.      Intellectual Curiosity. A researcher undertakes a deep thinking and inquiry

of the things, and situations around him.2.      Prudence. The researcher is careful to conduct his research study at the

right time and at the right place wisely, efficiently, and economically.3.      Healthy Criticism. The researcher is always doubtful as to the truthfulness of

the results.4.      Intellectual Honesty. An intelligent researcher is honest to collect or gather

data or facts in order to arrive at honest results.5.      Intellectual Creativity – A productive and resourceful investigator always

creates new researches.  Values of Research to Man1.      Research improves the quality of life.2.      Research improves instruction.3.      Research improves students’ achievement.

4.      Research improves teacher’s competence.5.      Research satisfies man’s needs.6.      Research reduces the burden of work.7.      Research has deep-seated psychological aspects.8.      Research improves the exportation of food products.9.      Research responds to the economic recovery and austerity measure of the

country.10.  Research trains graduates to become responsive to the economic

development of the country and to compete globally.  Types of Research1.      Basic Research. This is also called as “fundamental research” or “pure

research”. It seeks to discover basic truths or principles.Examples:

         Boyle’s Law         Charles’ Law         Archimedes’ Principle         Hooke’s Law         Newton’s Law2.      Applied Research. This type of research involves seeking new applications of

scientific knowledge to the solution of a problem, such as a development of a new system or procedure, new device, or new method in order to solve the problem.

3.      Developmental Research. This is a decision-oriented research involving the application of the steps of the scientific method in response to an immediate need to improve existing practices.

  Classification of Research1.      Library Research. This is done in the library where answers to specific

questions or problems of the study are available.2.      Field Research. Here, research is conducted in a natural setting.3.      Laboratory Research. The research is conducted in artificial or controlled

conditions by isolating the study in a thoroughly specified and equipped area. The purposes are: (1) to test hypotheses derived from theory, (2) to control variance under research conditions, and (3) to discover the relations between the dependent and the independent.THE VARIABLE

  Meaning of VariableA variable is defined as a quantity susceptible of fluctuation or change in value or magnitude under different conditions.

  Types of Variable1.      Independent Variable. This is the stimulus variable which is chosen by the

researcher to determine the relationship to an observed phenomenon.2.      Dependent Variable. This is the response variable which is observed and

measured to determine the effect of the independent variable.3.      Moderator Variable. This is a secondary or special type of independent

variable chosen by the researcher to determine if it changes or modifies the relationship between the independent and dependent variables.

4.      Control Variable. This is the variable that is controlled by the investigator in which the effects can be neutralized by eliminating or removing the variable.

5.      Intervening Variable. This is a variable which interferes with the independent and dependent variables, but its effects can either strengthen or weaken the independent and dependent variables.

  Components of the research process1.      Problem/ Objectives2.      Hypotheses3.      Theoretical/ Conceptual Framework4.      Assumptions5.      Review of Related Literature6.      Research Design7.      Data Collection8.      Data Processing and Statistical Treatment9.      Analysis and Interpretation10.  Summary, Conclusions and Recommendations

The frequency (f) of a particular observation is the number of times the observation occurs in the data. The distribution of a variable is the pattern of frequencies of the observation. Frequency distributions are portrayed as frequency tables, histograms, orpolygons.

Frequency distributions can show either the actual number of observations falling in each range or the percentage of observations. In the latter instance, the distribution is called arelative frequency distribution.

Frequency distribution tables can be used for both categorical and numeric variables. Continuous variables should only be used with class intervals, which will be explained shortly.

Example 1 – Constructing a frequency distribution table

A survey was taken on Maple Avenue. In each of 20 homes, people were asked how many cars were registered to their households. The results were recorded as follows:

1, 2, 1, 0, 3, 4, 0, 1, 1, 1, 2, 2, 3, 2, 3, 2, 1, 4, 0, 0

Use the following steps to present this data in a frequency distribution table.

1. Divide the results (x) into intervals, and then count the number of results in each interval. In this case, the intervals would be the number of households with no car (0), one car (1), two cars (2) and so forth.

2. Make a table with separate columns for the interval numbers (the number of cars per household), the tallied results, and the frequency of results in each interval. Label these columns Number of cars, Tally and Frequency.

3. Read the list of data from left to right and place a tally mark in the appropriate row. For example, the first result is a 1, so place a tally mark in the row beside where 1 appears in the interval column (Number of cars). The next result is a 2, so place a tally mark in the row beside the 2, and so on. When you reach your fifth tally mark, draw a tally line through the preceding four marks to make your final frequency calculations easier to read.

4. Add up the number of tally marks in each row and record them in the final column entitled Frequency.

Your frequency distribution table for this exercise should look like this:

Table 1. Frequency table for the number of cars registered in each household

Number of cars (x)

Tally Frequency (f)

0 4

1 6

2 5

3 3

4 2

By looking at this frequency distribution table quickly, we can see that out of 20 households surveyed, 4 households had no cars, 6 households had 1 car, etc.

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Example 2 – Constructing a cumulative frequency distribution table

A cumulative frequency distribution table is a more detailed table. It looks almost the same as a frequency distribution table but it has added columns that give the cumulative frequency and the cumulative percentage of the results, as well.

At a recent chess tournament, all 10 of the participants had to fill out a form that gave their names, address and age. The ages of the participants were recorded as follows:

36, 48, 54, 92, 57, 63, 66, 76, 66, 80

Use the following steps to present these data in a cumulative frequency distribution table.

1. Divide the results into intervals, and then count the number of results in each interval. In this case, intervals of 10 are appropriate. Since 36 is the lowest age and 92 is the highest age, start the intervals at 35 to 44 and end the intervals with 85 to 94.

2. Create a table similar to the frequency distribution table but with three extra columns.

In the first column or the Lower value column, list the lower value of the result intervals. For example, in the first row, you would put the number 35.

The next column is the Upper value column. Place the upper value of the result intervals. For example, you would put the number 44 in the first row.

The third column is the Frequency column. Record the number of times a result appears between the lower and upper values. In the first row, place the number 1.

The fourth column is the Cumulative frequency column. Here we add the cumulative frequency of the previous row to the frequency of the current row. Since this is the first row, the cumulative frequency is the same as the frequency. However, in the second row, the frequency for the 35–44 interval (i.e., 1) is added to the frequency for the 45–54 interval (i.e., 2). Thus, the cumulative frequency is 3, meaning we have 3 participants in the 34 to 54 age group.

1 + 2 = 3

The next column is the Percentage column. In this column, list the percentage of the frequency. To do this, divide the frequency by the total number of results and multiply by 100. In this case, the frequency of the first row is 1 and the total number of results is 10. The percentage would then be 10.0.

10.0. (1 ÷ 10) X 100 = 10.0

The final column is Cumulative percentage. In this column, divide the cumulative frequency by the total number of results and then to make a percentage, multiply by 100. Note that the last number in this column should always equal 100.0. In this example, the cumulative frequency is 1 and the total number of results is 10, therefore the cumulative percentage of the first row is 10.0.

10.0. (1 ÷ 10) X 100 = 10.0

3. The cumulative frequency distribution table should look like this:

Table 2. Ages of participants at a chess tournament

Lower Value

Upper Value

Frequency (f) Cumulative frequency

Percentage Cumulative percentage

35 44 1 1 10.0 10.0

45 54 2 3 20.0 30.0

55 64 2 5 20.0 50.0

65 74 2 7 20.0 70.0

75 84 2 9 20.0 90.0

85 94 1 10 10.0 100.0

For more information on how to make cumulative frequency tables, see the section onCumulative frequency and Cumulative percentage.

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Class intervals

If a variable takes a large number of values, then it is easier to present and handle the data by grouping the values into class intervals. Continuous variables are more likely to be presented in class intervals, while discrete variables can be grouped into class intervals or not.

To illustrate, suppose we set out age ranges for a study of young people, while allowing for the possibility that some older people may also fall into the scope of our study.

The frequency of a class interval is the number of observations that occur in a particular predefined interval. So, for example, if 20 people aged 5 to 9 appear in our study's data, the frequency for the 5–9 interval is 20.

The endpoints of a class interval are the lowest and highest values that a variable can take. So, the intervals in our study are 0 to 4 years, 5 to 9 years, 10 to 14 years, 15 to 19 years, 20 to 24 years, and 25 years and over. The endpoints of the first interval are 0 and 4 if the variable is discrete, and 0 and 4.999 if the variable is continuous. The endpoints of the other class intervals would be determined in the same way.

Class interval width is the difference between the lower endpoint of an interval and the lower endpoint of the next interval. Thus, if our study's continuous intervals are 0 to 4, 5 to 9, etc., the width of the first five intervals is 5, and the last interval is open, since no higher endpoint is assigned to it. The intervals could also be written as 0 to less than 5, 5 to less than 10, 10 to less than 15, 15 to less than 20, 20 to less than 25, and 25 and over.

Rules for data sets that contain a large number of observations

In summary, follow these basic rules when constructing a frequency distribution table for a data set that contains a large number of observations:

find the lowest and highest values of the variables decide on the width of the class intervals include all possible values of the variable.

In deciding on the width of the class intervals, you will have to find a compromise between having intervals short enough so that not all of the observations fall in the same interval, but long enough so that you do not end up with only one observation per interval.

It is also important to make sure that the class intervals are mutually exclusive.

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Example 3 – Constructing a frequency distribution table for large numbers of observations

Thirty AA batteries were tested to determine how long they would last. The results, to the nearest minute, were recorded as follows:

423, 369, 387, 411, 393, 394, 371, 377, 389, 409, 392, 408, 431, 401, 363, 391, 405, 382, 400, 381, 399, 415, 428, 422, 396, 372, 410, 419, 386, 390

Use the steps in Example 1 and the above rules to help you construct a frequency distribution table.

Answer

The lowest value is 363 and the highest is 431.

Using the given data and a class interval of 10, the interval for the first class is 360 to 369 and includes 363 (the lowest value). Remember, there should always be enough class intervals so that the highest value is included.

The completed frequency distribution table should look like this:

Table 3. Life of AA batteries,

in minutes

Battery life, minutes (x)

Tally Frequency (f)

360–369 2

370–379 3

380–389 5

390–399 7

400–409 5

410–419 4

420–429 3

430–439 1

Total 30

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Relative frequency and percentage frequency

An analyst studying these data might want to know not only how long batteries last, but also what proportion of the batteries falls into each class interval of battery life.

This relative frequency of a particular observation or class interval is found by dividing the frequency (f) by the number of observations (n): that is, (f ÷ n). Thus:

Relative frequency = frequency ÷ number of observations

The percentage frequency is found by multiplying each relative frequency value by 100. Thus:

Percentage frequency = relative frequency X 100 = f ÷ n X 100

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Example 4 – Constructing relative frequency and percentage frequency tables

Use the data from Example 3 to make a table giving the relative frequency and percentage frequency of each interval of battery life.

Here is what that table looks like:

Table 4. Life of AA batteries, in minutes

Battery life, minutes (x) Frequency (f) Relative frequency Percent frequency

360–369 2 0.07 7

370–379 3 0.10 10

380–389 5 0.17 17

390–399 7 0.23 23

400–409 5 0.17 17

410–419 4 0.13 13

420–429 3 0.10 10

430–439 1 0.03 3

Total 30 1.00 100

An analyst of these data could now say that:

7% of AA batteries have a life of from 360 minutes up to but less than 370 minutes, and that

the probability of any randomly selected AA battery having a life in this range is approximately 0.07.

Keep in mind that these analytical statements have assumed that a representative sample was drawn. In the real world, an analyst would also refer to an estimate of variability (see

section titled Measures of spread) to complete the analysis. For our purpose, however, it is enough to know that frequency distribution tables can provide important information about the population from which a sample was drawn.

Frequency

Frequency is how often something occurs.

Example: Sam played football on

Saturday Morning,

Saturday Afternoon

Thursday Afternoon

The frequency was 2 on Saturday, 1 on Thursday and 3 for the whole week.

Frequency Distribution

By counting frequencies we can make a Frequency Distribution table.

Example: Goals

Sam's team has scored the following numbers of goals in recent games:

2, 3, 1, 2, 1, 3, 2, 3, 4, 5, 4, 2, 2, 3

 

Sam put the numbers in order, 

then added up:

how often 1 occurs (2

times),

how often 2 occurs (5

times),

etc,

and wrote them down as a 

Frequency Distribution table.

From the table we can see interesting things such as

getting 2 goals happens most often

only once did they get 5 goals

This is the definition:

Frequency Distribution: values and their frequency (how often each value

occurs).

Here is another example:

Example: Newspapers

These are the numbers of newspapers sold at a local shop over the last 10 days:

22, 20, 18, 23, 20, 25, 22, 20, 18, 20

Let us count how many of each number there is:

Papers Sold Frequency

18 2

19 0

20 4

21 0

22 2

23 1

24 0

25 1

It is also possible to group the values. Here they are grouped in 5s:

Papers Sold Frequency

15-19 2

20-24 7

25-29 1

(Learn more about  Grouped Frequency Distributions )

Graphs

After creating a Frequency Distribution table you might like to make a  Bar

Graph  or a  Pie Chart  using the  Data Graphs (Bar, Line and Pie)  page.

 

Elements of a research proposal and report

2005 © David S. Walonick, Ph.D.

All rights reserved.

Excerpts from Survival Statistics - an applied statistics book for graduate students.

All research reports use roughly the same format. It doesn't matter whether you've done a customer

satisfaction survey, an employee opinion survey, a health care survey, or a marketing research survey. All

have the same basic structure and format. The rationale is that readers of research reports (i.e., decision

makers, funders, etc.) will know exactly where to find the information they are looking for, regardless of

the individual report.

Once you've learned the basic rules for research proposal and report writing, you can apply them to any

research discipline. The same rules apply to writing a proposal, a thesis, a dissertation, or any business

research report.

The Research Proposal and Report

General

Style, layout, and page formatting

Outline of the chapters and sections

Chapter I - Introduction

Chapter II - Background

Chapter III - Methodology

Chapter IV - Results

Chapter V - Conclusions and Recommendations

General considerations

Research papers usually have five chapters with well-established sections in each chapter. Readers of

the paper will be looking for these chapters and sections so you should not deviate from the standard

format unless you are specifically requested to do so by the research sponsor.

Most research studies begin with a written proposal. Again, nearly all proposals follow the same format. In

fact, the proposal is identical to the first three chapters of the final paper except that it's writtten in future

tense. In the proposal, you might say something like "the researchers will secure the sample from ...",

while in the final paper, it would be changed to "the researchers secured the sample from ...". Once again,

with the exception of tense, the proposal becomes the first three chapters of the final research paper.

The most commonly used style for writing research reports is called "APA" and the rules are described in

thePublication Manual of the American Psychological Association. Any library or bookstore will have it

readily available. The style guide contains hundreds of rules for grammar, layout, and syntax. This paper

will cover the most important ones.

Avoid the use of first person pronouns. Refer to yourself or the research team in third person. Instead of

saying "I will ..." or "We will ...", say something like "The researcher will ..." or "The research team will ...".

A suggestion: Never present a draft (rough) copy of your proposal, thesis, dissertation, or research

paper...even if asked. A paper that looks like a draft, will interpreted as such, and you can expect

extensive and liberal modifications. Take the time to put your paper in perfect APA format before showing

it to anyone else. The payoff will be great since it will then be perceived as a final paper, and there will be

far fewer changes.

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Style, layout, and page formatting

Title page

All text on the title page is centered vertically and horizontally. The title page has no page number and it is

not counted in any page numbering.

Page layout

Left margin: 1½"

Right margin: 1"

Top margin: 1"

Bottom margin: 1"

Page numbering

Pages are numbered at the top right. There should be 1" of white space from the top of the page number

to the top of the paper. Numeric page numbering begins with the first page of Chapter 1 (although a page

number is not placed on page 1).

Spacing and justification

All pages are single sided. Text is double-spaced, except for long quotations and the bibliography (which

are single-spaced). There is one blank line between a section heading and the text that follows it. Do not

right-justify text. Use ragged-right.

Font face and size

Any easily readable font is acceptable. The font should be 10 points or larger. Generally, the same font

must be used throughout the manuscript, except 1) tables and graphs may use a different font, and 2)

chapter titles and section headings may use a different font.

References

APA format should be used to cite references within the paper. If you name the author in your sentence,

then follow the authors name with the year in parentheses. For example:

Jones (2004) found that... 

If you do not include the authors name as part of the text, then both the author's name and year are

enclosed in parentheses. For example: 

One researcher (Jones, 2004) found that...

A complete bibliography is attached at the end of the paper. It is double spaced except single-spacing is

used for a multiple-line reference. The first line of each reference is indented.

Examples:

     Bradburn, N. M., & Mason, W. M. (1964). The effect of question order on response. Journal of

Marketing Research 1 (4), 57-61.

     Bradburn, N. M., & Miles, C. (1979). Vague quantifiers. Public Opinion Quarterly 43 (1), 92-101.

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Outline of chapters and sections

TITLE PAGE

TABLE OF CONTENTS

CHAPTER I - Introduction

     Introductory paragraphs

     Statement of the problem

     Purpose

     Significance of the study

     Research questions and/or hypotheses

CHAPTER II - Background

     Literature review

     Definition of terms

CHAPTER III - Methodology

     Restate purpose and research questions or null hypotheses

     Population and sampling

     Instrumentation (include copy in appendix)

     Procedure and time frame

     Analysis plan (state critical alpha level and type of statistical tests)

     Validity and reliability

     Assumptions

     Scope and limitations

CHAPTER IV - Results

CHAPTER V - Conclusions and recommendations

     Summary (of what you did and found)

     Discussion (explanation of findings - why do you think you found what you did?)

     Recommendations (based on your findings)

REFERENCES

APPENDIX

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Chapter I - Introduction

Introductory paragraphs

Chapter I begins with a few short introductory paragraphs (a couple of pages at most). The primary goal

of the introductory paragraphs is to catch the attention of the readers and to get them "turned on" about

the subject. It sets the stage for the paper and puts your topic in perspective. The introduction often

contains dramatic and general statements about the need for the study. It uses dramatic illustrations or

quotes to set the tone. When writing the introduction, put yourself in your reader's position - would you

continue reading?

Statement of the Problem

The statement of the problem is the focal point of your research. It is just one sentence (with several

paragraphs of elaboration).

You are looking for something wrong.

     ....or something that needs close attention

     ....or existing methods that no longer seem to be working.

Example of a problem statement:

"The frequency of job layoffs is creating fear, anxiety, and a loss of productivity in middle management

workers."

While the problem statement itself is just one sentence, it is always accompanied by several paragraphs

that elaborate on the problem. Present persuasive arguments why the problem is important enough to

study. Include the opinions of others (politicians, futurists, other professionals). Explain how the problem

relates to business, social or political trends by presenting data that demonstrates the scope and depth of

the problem. Try to give dramatic and concrete illustrations of the problem. After writing this section, make

sure you can easily identify the single sentence that is the problem statement.

Purpose

The purpose is a single statement or paragraph that explains what the study intends to accomplish. A few

typical statements are:

The goal of this study is to...

     ... overcome the difficulty with ...

     ... discover what ... 

     ... understand the causes or effects of ...

     ... refine our current understanding of ...

     ... provide a new interpretation of ...

     ... understand what makes ___ successful or unsuccessful

Significance of the Study

This section creates a perspective for looking at the problem. It points out how your study relates to the

larger issues and uses a persuasive rationale to justify the reason for your study. It makes the purpose

worth pursuing. The significance of the study answers the questions:

     Why is your study important?

     To whom is it important?

     What benefit(s) will occur if your study is done?

Research Questions and/or Hypotheses and/or Null Hypotheses

Chapter I lists the research questions (although it is equally acceptable to present the hypotheses or null

hypotheses). No elaboration is included in this section. An example would be:

The research questions for this study will be:

     1. What are the attitudes of...

     2. Is there a significant difference between...

     3. Is there a significant relationship between...

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Chapter II - Background

Chapter II is a review of the literature. It is important because it shows what previous researchers have

discovered. It is usually quite long and primarily depends upon how much research has previously been

done in the area you are planning to investigate. If you are planning to explore a relatively new area, the

literature review should cite similar areas of study or studies that lead up to the current research. Never

say that your area is so new that no research exists. It is one of the key elements that proposal readers

look at when deciding whether or not to approve a proposal.

Chapter II should also contain a definition of terms section when appropriate. Include it if your paper uses

special terms that are unique to your field of inquiry or that might not be understood by the general

reader. "Operational definitions" (definitions that you have formulated for the study) should also be

included. An example of an operational definition is: "For the purpose of this research, improvement is

operationally defined as posttest score minus pretest score".

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Chapter III - Methodology

The methodology section describes your basic research plan. It usually begins with a few short

introductory paragraphs that restate purpose and research questions. The phraseology should be

identical to that used in Chapter I. Keep the wording of your research questions consistent throughout the

document.

Population and sampling

The basic research paradigm is: 

     1) Define the population

     2) Draw a representative sample from the population

     3) Do the research on the sample

     4) Infer your results from the sample back to the population

As you can see, it all begins with a precise definition of the population. The whole idea of inferential

research (using a sample to represent the entire population) depends upon an accurate description of the

population. When you've finished your research and you make statements based on the results, who will

they apply to? Usually, just one sentence is necessary to define the population. Examples are: "The

population for this study is defined as all adult customers who make a purchase in our stores during the

sampling time frame", or "...all home owners in the city of Minneapolis", or "...all potential consumers of

our product".

While the population can usually be defined by a single statement, the sampling procedure needs to be

described in extensive detail. There are numerous sampling methods from which to choose. Describe in

minute detail, how you will select the sample. Use specific names, places, times, etc. Don't omit any

details. This is extremely important because the reader of the paper must decide if your sample will

sufficiently represent the population.

Instrumentation

If you are using a survey that was designed by someone else, state the source of the survey. Describe

the theoretical constructs that the survey is attempting to measure. Include a copy of the actual survey in

the appendix and state that a copy of the survey is in the appendix.

Procedure and time frame

State exactly when the research will begin and when it will end. Describe any special procedures that will

be followed (e.g., instructions that will be read to participants, presentation of an informed consent form,

etc.).

Analysis plan

The analysis plan should be described in detail. Each research question will usually require its own

analysis. Thus, the research questions should be addressed one at a time followed by a description of the

type of statistical tests that will be performed to answer that research question. Be specific. State what

variables will be included in the analyses and identify the dependent and independent variables if such a

relationship exists. Decision making criteria (e.g., the critical alpha level) should also be stated, as well as

the computer software that will be used.

Validity and reliability

If the survey you're using was designed by someone else, then describe the previous validity and

reliability assessments. When using an existing instrument, you'll want to perform the same reliability

measurement as the author of the instrument. If you've developed your own survey, then you must

describe the steps you took to assess its validity and a description of how you will measure its reliability.

Validity refers to the accuracy or truthfulness of a measurement. Are we measuring what we think we

are? There are no statistical tests to measure validity. All assessments of validity are subjective opinions

based on the judgment of the researcher. Nevertheless, there are at least three types of validity that

should be addressed and you should state what steps you took to assess validity.

Face validity refers to the likelihood that a question will be misunderstood or misinterpreted. Pretesting a

survey is a good way to increase the likelihood of face validity. One method of establishing face validity is

described here. How to make sure your survey is valid.

Content validity refers to whether an instrument provides adequate coverage of a topic. Expert opinions,

literature searches, and pretest open-ended questions help to establish content validity.

Construct validity refers to the theoretical foundations underlying a particular scale or measurement. It

looks at the underlying theories or constructs that explain a phenomena. In other words, if you are using

several survey items to measure a more global construct (e.g., a subscale of a survey), then you should

describe why you believe the items comprise a construct. If a construct has been identified by previous

researchers, then describe the criteria they used to validate the construct. A technique known as

confirmatory factor analysis is often used to explore how individual survey items contribute to an overall

construct measurement.

Reliability is synonymous with repeatability or stability. A measurement that yields consistent results over

time is said to be reliable. When a measurement is prone to random error, it lacks reliability.

There are three basic methods to test reliability : test-retest, equivalent form, and internal consistency.

Most research uses some form of internal consistency. When there is a scale of items all attempting to

measure the same construct, then we would expect a large degree of coherence in the way people

answer those items. Various statistical tests can measure the degree of coherence. Another way to test

reliability is to ask the same question with slightly different wording in different parts of the survey. The

correlation between the items is a measure of their reliability. See: How to test the reliability of a survey.

Assumptions

All research studies make assumptions. The most obvious is that the sample represents the population.

Another common assumptions are that an instrument has validity and is measuring the desired

constructs. Still another is that respondents will answer a survey truthfully. The important point is for the

researcher to state specifically what assumptions are being made.

Scope and limitations

All research studies also have limitations and a finite scope. Limitations are often imposed by time and

budget constraints. Precisely list the limitations of the study. Describe the extent to which you believe the

limitations degrade the quality of the research.

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Chapter IV - Results

Description of the sample

Nearly all research collects various demographic information. It is important to report the descriptive

statistics of the sample because it lets the reader decide if the sample is truly representative of the

population.

Analyses

The analyses section is cut and dry. It precisely follows the analysis plan laid out in Chapter III. Each

research question addressed individually. For each research question:

     1) Restate the research question using the exact wording as in Chapter I

     2) If the research question is testable, state the null hypothesis

     3) State the type of statistical test(s) performed

     4) Report the statistics and conclusions, followed by any appropriate table(s)

Numbers and tables are not self-evident. If you use tables or graphs, refer to them in the text and explain

what they say. An example is: "Table 4 shows a strong negative relationship between delivery time and

customer satisfaction (r=-.72, p=.03)". All tables and figures have a number and a descriptive heading.

For example:

Table 4

The relationship between delivery time and customer satisfaction.

Avoid the use of trivial tables or graphs. If a graph or table does not add new information (i.e., information

not explained in the text), then don't include it.

Simply present the results. Do not attempt to explain the results in this chapter.

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Chapter V - Conclusions and recommendations

Begin the final chapter with a few paragraphs summarizing what you did and found (i.e., the conclusions

from Chapter IV).

Discussion

Discuss the findings. Do your findings support existing theories? Explain why you think you found what

you did. Present plausible reasons why the results might have turned out the way they did.

Recommendations

Present recommendations based on your findings. Avoid the temptation to present recommendations

based on your own beliefs or biases that are not specifically supported by your data. Recommendations

fall into two categories. The first is recommendations to the study sponsor. What actions do you

recommend they take based upon the data. The second is recommendations to other researchers. There

are almost always ways that a study could be improved or refined. What would you change if you were to

do your study over again? These are the recommendations to other researchers.

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References

List references in APA format alphabetically by author's last name

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Appendix

Include a copy of any actual instruments. If used, include a copy of the informed consent form.

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