This document outlines the key sections that should be included in a Chapter 3 methodology section of a research paper. These include: research design/methodology, research locale, subject/respondents of the study, sampling procedure/sample size, instruments used for data collection, treatment of collected data, and ethical considerations of the research study. Common research methodologies, sampling techniques, data analysis strategies, and tips for writing Chapter 3 are also discussed at length.

1. Chapter 3
Methodology

2. What are the sections
in Chapter 3
 Research Design/Methodology
 Research Locale
 Subject/respondents of the Study
 Sampling procedure/sample size
 Instruments Used; scoring procedures
 Conduct of the study
 Ethical considerations
 Treatment of Data

3. Research Design
 Research design is the plan or method which the
researcher used in answering the problems set in the
study and in the conduct of the research.
 This is categorized as to the procedure upon which
the researcher collects and analyzes the data.
 The two broad categories for research designs are
the QUALITATIVE research and the QUANTITATIVE
research.
 Both have their own merits and flaws, but they could
be complimentary to each other.

4. Research Methodologies
 Descriptive Research
 Correlational
 Causal-comparative
 Historical
 Experimental Research

5. Research Locale
 The research locale indicates the place or
location where the study is conducted or
undertaken.
 Its description should have relevance to the
topic/content of the study.
 The locale could indicate the population, the
boundaries and the variables.
 In many instances, the researcher provides a
map for its geographical illustration.

6.  When this is done, the map should
reflect what the researcher highlights in
the study.
 This map should be accurately plotted
out with correct scaling and legends,
otherwise if the locale is adequately
describe, the map could be omitted.

7. Subject of the study
 The subject of the study could be “people” or
“non-people”.
 For people it can either be taken from
population.
 If the total population is very large then the
sampling is used.
 The researcher should describe the subject of
the study as to the size of the population or
the sampling

8. Respondents
 The respondents are those who
participate in answering the
instruments used in the study. The
respondents could also be the subjects
of the study, hence sometimes the
subheading for this section is the
subject-respondents.

9. Sampling Procedure
 In conducting a research work we are often
faced with the dilemma on what constitute a
reliable and acceptable sampling. When the
population to be studied is very small, we do
not need to get a sample, as we can take the
whole population. This is because the
population size is manageable. There are
instances when we take the whole population
even if it is very large, and this happens when
we conduct a census.

10. Population
 Gay (1976) defines a population as a
group to which the researcher would
like the result of a study to be
applicable to the general body. He
used the word “generalizable”.
 Kerlinger (1973) defines population as
all members of any well-defined class of
people, events or objects.

11. Sample
 Ferguson (1976) defines a sample as
any sub aggregate drawn from a
population. It is the small group that you
observe from a given population where
your generalization is made.

12. Sampling
 Sampling (Ary, Jacob and Razavieh) is the
process which involves taking a part of the
population by making observations on this
representative group and generalizing the
findings to the bigger population.
 It refers to strategies which enable one to
pick a subgroup from a larger group and then
use this subgroup as a basis for making
judgment about the larger group (Vockell,
1983)

13. The steps used in sampling
 identification of a population,
determination of a required sample
size
 selection of a sample.

14. Sample size
 Slovin’s Formula
 n = N/(1+Ne2)
where n = sample size, N = population size, and e =
desired margin of error, which is the percent
allowance for non precision because of the use of the
sample instead of the population.
For example, in a population of 9000 and a margin of
error set at 2%
n = 9000/[1 + 9000 (.02)2]
n = 1,957

15. Sampling Strategies
 Probability
 simple random sampling
 lottery
 systematic sampling
 stratified sampling, cluster sampling.

16.  Non-probability sampling
 Purposive or deliberate sampling. This is
sampling taken on purpose.
 Quota sampling. One identifies a set of
important characteristics of a population
and then select the desired sample in a non
random way until the quota is reach.
 Convenience sampling. This is based on
the convenience of the researcher, like
through telephone, or survey, etc.

17. Instruments
 Questionnaires requires the respondents to
write or answer questions
 Checklists -respondents are given a list of
items where they simply check based from
the given question
 Interviews are done by the researcher orally
to get information about some
issues/concerns.

18.  Focus Group Discussion/Interview is a
carefully planned and moderated informal
discussion where one person’s ideas bounce
off another’s creating a chain of relation of
informative dialogue
 Observations are concerned with the
recording of events and behaviors of those
being studied in their natural setting

19.  Semantic Differential – rating scale
designed to measure the connotative
meaning of things, events and concepts
 Q-sort is ranking of variables typically
printed on cards according to some
instructions
 Likert Scale – scale showing agrrement
or disagreement of attitudes or opinions

20. Treatment of data
 Could be qualitative or quantitative
 Statistical treatment makes use of
statistical tools and techniques to
discover relationships between
variables, develop generalizations that
may be used to explain phenomenon,
and predict future occurrences.

21.  Descriptive statistics are those that
involve mere counting and tabulation
like frequency counts, percentages,
averages, spreads.
 Inferential statistics requires statistical
tests of significance where one can
make inferences. It can be parametric
or non-parametric

22.  Parametric tests are the z-test, t-test and F-
test.
 Non-parametric tests do not depend always
on specific type of distribution like the normal
curve. They are also called distribution-free
statistics, applied to both nominal and ordinal
data.
 The chi-square is a commonly used non-
parametric test

23. Mean and Standard Deviation
 Mean gives the average of the data
 Standard deviation - Considered as the
most useful index of variability or
dispersion

24. Test for comparison
– Test whether the coefficient of
correlation is significant at a particular
level
– T-test for difference between means (t-
test for independent means, t-test for
dependent means

25. Analysis of Variance
– To determine if there are significant differences
among the means of more than two groups;
ANOVA; The F-value is the ratio of two
variances or mean squares
– MANOVA – multivariate analysis of variance -
general form of analysis of variance which
incorporates two or more independent variables
in the same analysis

26. Different correlational
techniques
 Pearson-product moment correlation –
measure of relationship between two
variables that are usually of the interval
type of data
 Spearman Rank-order correlation
coefficient- measure of correlation
between two sets of ordered pairs

27.  Kendall’s tau – measure o correlation
between ranks
 Kendall’s coefficient of concordance – useful
to determine the relationship among three or
more sets of ranks
 Point-biserial coefficient special type of
Pearson product moment correlation
coefficient widely use d in test construction,
test validation and analysis

28.  Biserial correlation coefficient – used In test
construction, test validation and analysis like
the point biserial coefficient
 Phi coefficient –sometimes called fourfold
coefficient used when each of the variables
are dichotomous
 Tetrachoric correlation coefficient – measure
of correlation between data that can be
reduced to two dichotomies

29.  Partial correlation – whenever 2 or more variables
are correlated, there may be possibility that yet other
variables may explain any relationship that are found
 Multiple regression – technique that enables
researches to determine a correlation between a
criterion variable (dependent) and the best
combination of two or more predictor variables
(independent)
 Coefficient of multiple correlation - indicates the
strength of the correlation between the combination
of the predictor variables and the criterion variable

30.  Coefficient of determination – symbolized by r2, the
coefficient of determination is the square of the
correlation between one predictor variable and a
criterion variable
 Discriminant function analysis – technique used in
similar fashion as the multiple regression analysis
 Factor analysis – technique that allows to determine
if many variables can be described by a few factors
 Path analysis – used to test the possibility of a causal
connection among three or more variables

31. Some non-parametric
techniques
 Techniques for independent samples: The
median test – applied to see if two groups
come from population having the same
median; The Mann-Whitney U test – non
parametric equivalent to the t-test when one
is dealing with ordinal data; The Kruskal-
Wallis One way Analysis of Variance - non
parametric equivalent to the One-way ANOVA
when one is dealing with ordinal data

32.  Techniques for dependent samples:
 The sign test non-parametric equivalent test
for t-test for dependent or correlated samples.
 The Wilcoxon’s Matched pairs Signed ranks
test – is quite similar to the sign test; more
powerful and efficient since it combines the
sign of the difference with the relative size of
the difference;

33.  The Friedman Two way Analysis of
variance – both sign test and
Wilcoxon’s matched pairs signed-ranks
tests are used for two correlated
samples.
 In case there are three or more
correlated or matched groups involved
the Friedman Two-way ANOVA is
appropriate

34. Tips for writing Chapter 3
 First, examine the problems you set in the study
 Check the type of research methodology based from
the problems
 Conduct a needs assessment
 Know how to describe the locale in relation to the
study
 Determine the subject-respondents, sample size
from the given population in your study

35.  Decide on what instrument to use. Surf the
net to check if there are available instruments
 Prepare the instruments, have these checked,
tried-out, validated. Get the reliability when
needed.
 Consider the scoring procedure, the criteria
used, and the rating scale
 Get the approval of the thesis committee prior
to the launching of instrument

36.  Get appropriate and adequate sample
size to launch the instrument
 Retrieve the accomplished
questionnaire; survey; etc.
 If interview/FGD is conducted transcribe
the discourses

37.  Tabulate the data/ put the transcriptions
in matrices
 Determine the treatment of data to be
utilized for analysis
 Analyze the results based from the
scoring criteria/descriptive ratings/
qualifying statements

38. Remember
 Always follow correct technical format
 Be systematic and succinct in the
discussion on the procedures
 Be clear and consistent in your
presentations
 Maps and figures have to be clear and
accurate

39.  The conduct of the study have to be
discussed in detailed to guide the
reader
 Avoid being repetitive
 Check sentences and edit your work.
You can ask another person to read
your write-up if this could be
understood.

40.  Research ethics have to be strictly
followed
 Informed consent form should be
accomplished by the respondents of the
study, especially for minors.
 Follow correct protocol. Be courteous in
the conduct of the study.

41. Work Activity
Write Chapter 3 of your research paper to
include
 Research methodology/design
 Locale
 Subject/respondents
 Instruments
 Conduct of the study
 Treatment of data