The document provides an overview of a research methodology and statistics course. It outlines the course objectives, which are to provide an understanding of research methodology and enable students to apply it to forensic science. It also lists the course outcomes, which are for students to be able to recall research objectives and types, appraise sampling methods and research design, conduct primary and secondary data collection, and perform descriptive and inferential statistics. The document further details the topics to be covered in each unit, such as introduction to research methodology, sampling design, data collection, and statistics. It provides teaching methods, timelines and an overview of the content to be covered in each unit.

1. Research
Methodology and
Statistics
Dr. Suchita Rawat
MPhil, NET, PhD

2. Course Objectives
To provide an understanding of research methodology
To enable students to apply research methodology to the field of
forensic science
Course Outcomes
After the successful completion of the course, the student will
be able to:
CO1 : to recall and recognize the objectives, motivations, and types
of research
CO2 : appraise the methods of sampling and research design
CO3 : develop and execute primary and secondary data collection
CO4 : Test and validate descriptive and inferential statistics on
continuous and categorical

3. Unit /Topic No. OF
HOURS
TEACHING METHODOLOGY TIME OF
COMPLETION
Unit 1: Introduction to Research
Methodology
15 Mapped to Ms. Aditi
Unit 2: Research and Sampling Design
(Steps in Sampling Design; Criteria of
Selecting a Sampling Procedure; 10
Characteristics of a Good Sample Design;
Types of Sample Designs; Hypothesis
formulation and testing)
10 Co shared with Ms. Aditi
Participatory TL: Interactive Lecture,
Guided library work, Technical
presentation
Aug 14- Aug 19, 2023
Unit 3: Data Collection 8 Participatory TL: Interactive Lecture,
Guided library work, Technical
presentation
Sep 4- Sep 9, 2023
Unit 4: Descriptive Statistics and Inferential
Statistics
12 Participatory TL: Interactive Lecture,
,Guided library work,
Technical presentation
Experiential TL: workshop
Oct 30 – Oct 31, 2023

4. Unit 2: Research and
Sampling Design
Unit 3: Data Collection Unit 4: Descriptive Statistics
and Inferential Statistics
Sampling Design; Criteria of
Selecting a Sampling
Procedure; Characteristics of a
Good Sample Design; Types of
Sample Designs; Hypothesis
formulation and testing.
Sampling Design; Criteria of
Selecting a Sampling
Procedure; 10 Characteristics
of a Good Sample Design;
Types of Sample Designs;
Hypothesis formulation and
testing.
Statistics in research;
Measures of Central Tendency;
Measures of Dispersion;
Measures of Asymmetry;
Measures of Relationship;
Simple Regression Analysis;
Multiple Correlation and
Regression; t-test; Chi square
test; ANOVA; Introduction to
Statistical Package for Social
Sciences (SPSS)

7. Sampling techniques are methods used to select a
representative subset (sample) from a larger population
for the purpose of conducting research, analysis, or
making inferences about the entire population.

8. Some of the key advantages of sampling include:
Time and Cost Efficiency
Feasibility
Accuracy if representative of the population
Ethical Considerations (potential harm or invasion of
privacy)
Practicality for Data Analysis
Generalization (in a representative and unbiased)
Accessibility

9. Important terminology
Population.
• The entire group or set of individuals, items, or elements from which the
sample is drawn, and the results are generalized.
Sampling Frame
• A list or representation of all the elements in the population from which
the sample is drawn. It is the actual source used to select the sample.
Sample
• A subset of the population that is selected for study or analysis. The
sample represents the larger population, and conclusions drawn from the
sample are extrapolated to the population.
Sampling Unit
• The individual element or item in the population that can be selected in
the sampling process. It can be a person, household, product, or any other
discrete entity.

10. Criteria of Selecting a Sampling Procedure
Representativeness: sample is a true reflection of the
population's characteristics
Randomness : each individual in the population has an
equal chance of being selected for the sample/avoid bias
Precision: close the sample's results are to the true
population values
Feasibility: The chosen sampling procedure should be
feasible in terms of time, budget, and resources.
Research Objectives
Accessibility:availability of a sampling frame
Homogeneity
Ethical Considerations

11. Classification of Sampling

12. ‘Stratified Random Sampling’,
and
‘Stratified Proportional
Sampling’.
Lottery and Tippet’s Table

13. Sampling
technique
Advantages Disadvantages
Simple
Random
Sampling
1. It is hassle-free method of sampling
population is homogeneous.
2. b. There is no chance of personal bias of the
researcher to influence
3. requires no computation of any sort
1. It cannot be used in heterogeneous population.
2. It cannot be used where researcher wants to
conduct a mini-comparison within the universe by
studying the sample in divisions.
3. It requires basic knowledge of the universe, to
make a list to be able to choose from
Systemic
Sampling
1. This method is easy to understand and use.
2. b. This method involves least number of
steps.
3. There is least chance of influence of
personal bias of researcher.
4. No knowledge of the universe is required
before sampling
1. Every unit in the universe does not have equal
chances of being selected in the sample as the
selection depends on the ‘n’ number chosen.
2. It is not an effective sampling method in case of
heterogeneous population.

14. Sampling
technique
Advantages Disadvantages
Stratified
Sampling
1. There is better representation of the
different characteristics of the population.
2. The researcher can use results from
different strata to compare results within
the universe.
1. it involves more time as samples are to be taken
out from each strata to form the final sample
Cluster
sampling
1. It is useful where the population is divisible
into clusters, even heterogeneous clusters.
2. useful in large geographical areas.
3. As division of clusters is not dependent on
them being homogeneous. Therefore, more
than one characteristic can be studied in
one cluster.
4. There is no need to have a prior knowledge
of the population.
1. The clusters are not equal in size, so the final
sample may not represent the population
proportionately. Even if the study is conducted in
multi- phase manner, the clusters do not offer a
comparative analysis.
2. There is a possibility that a same person may form
part of more than one cluster. This will lead to
over representativeness.
3. there is a possibility that some clusters may be
homogeneous while other may be heterogeneous

16. Sampling
technique
Advantages Disadvantages
Convenience
sampling
1. suited for those researches
which are preliminary or pilot
projects, and which will be
supplemented with further
probability sampling research.
1. Low Diversity: tends to attract participants who are
readily accessible or willing to participate, leading to a
sample that lacks diversity in terms of demographics,
opinions, or experiences.
Purposive
sampling
1. It is easy on the pocket, as the
researcher chooses the units
himself/herself. There is no cost
involved in selecting units for
sample.
2. No prior knowledge of the
universe is required.
1. Representativeness of the sample is questionable.
2. It is not useful in cases of heterogeneous population.
3. Sampling may be influenced by the personal bias of the
researcher

17. Sampling
technique
Advantages Disadvantages
Quota sampling 1. The advantage of quota
sampling is its cost and time
efficacy.
2. It is one of the most effective
sampling, for small scale as
well as large scale sampling.
1. Lack of Representativeness
2. Determining the appropriate quotas can be challenging,
especially if the characteristics being targeted for quota
setting are interconnected or difficult to define
Snow ball
sampling
1. Access to Hard-to-Reach
Populations:
2. Cost-Effective
3. Quick Data Collection
1. Limited Control: Researchers have limited control over
the sampling process, as it relies heavily on
participants' referrals.

18. Principles and Precautions
of Sampling
The universe must be clearly defined.
The sampling units must be distinct and independent of
each other.
A clearly chalked out sampling design ensures
predetermined steps, and also encompasses planning for
contingencies.
Sampling must be done in an unbiased, objective and
systematic manner.
The objective of the research must be kept in mind while
sampling.
Arbitrary alterations must be avoided during sampling.
Sample size must be chosen in accordance with the nature of
study, i.e. qualitative or quantitative, and taking into
consideration the size of the universe.

19. Principles and Precautions
of Sampling
❑ The cost and time factor is an important influencing
factor in research. It is advisable to not see these factors
as an impediment to research, but to utilise them in the
most efficient way possible.
❑ Ease of contacting the respondents is another
important factor that is to be taken into consideration
while sampling.
❑ Even with the advent of technology, care must be taken
by the researcher that the selected respondents are
source of objective, unbiased answers.
❑ It should also be ensured to maximum possible extent
that the potential respondents are not being forced for
participation in the research.
❑ Sampling errors (in sample size, proportions) must be
avoided as much as possible.

20. Characteristics of a Good Sample
Design
Representativeness Randomization Adequate Sample Size
Sampling Frame: A clear
and accurate sampling
frame, which is a list of all
the potential individuals
or units in the population
Sampling Method:
should align with the
research objective
Sample Variability:
considers the variability
within the population.
Avoidance of Bias: non-
response bias, selection
bias, or measurement
bias.
Ethical Considerations:
Participants' rights and
informed, privacy and
confidentiality
Clear Sampling Plan
Pilot Testing: help
identify any potential
issues or areas for
improvement in the
sampling process.

21. HYPOTHESIS
A hypothesis is a specific, testable, and
falsifiable statement or proposition that
predicts a relationship between variables or
anticipates an outcome in a research study.
It serves as a tentative explanation that
researchers aim to confirm or reject through
empirical observation and analysis.
Testable
Specific
(clear and precise)
Falsifiable
(capable of being
proven wrong through
evidence)
Predictive
(Relationship or effect
between variables)
Empirical
(Observations,
existing theories, or
logical reasoning)
Verifiable(observable
and measurable
results)

22. Hypothesis Formulation
Identify the
Research
Problem
Literature Review
(understand gap
in literature)
Formulate the
Hypothesis: Null
and alternative
hypothesis
Specify Variables:
Clearly define the
independent
variable(s) and the
dependent
variable(s)
Directional vs.
Non-Directional
Hypotheses
Research Question: Does the new drug lead to a decrease in blood pressure?
Example of a Directional Hypothesis:
The new drug leads to a decrease in blood pressure.
Example of a Non Directional Hypothesis:
There is a relationship between new drug and blood pressure.

25. Types of Hypothesis
•Simple hypothesis: This type of hypothesis suggests
that there is a relationship between one independent
variable and one dependent variable.
Eg. "Students who eat breakfast will perform
better on a math exam than students who do not
eat breakfast.“
•Complex hypothesis: This type of hypothesis suggests a
relationship between three or more variables, such as
two independent variables and a dependent variable.
Eg. "People with high-sugar diets and sedentary
activity levels are more likely to develop
depression."

26. Null hypothesis: This hypothesis suggests
no relationship exists between two or
more variables.
Eg. "Children who receive a new
reading intervention will have no
difference in the scores.“
•Alternative hypothesis: This hypothesis
states the opposite of the null hypothesis.
Eg. "Children who receive a new
reading intervention will perform
better than students who did not
receive the intervention."

27. Statistical hypothesis: This hypothesis uses statistical
analysis to evaluate a representative sample of the
population and then generalizes the findings to the larger
group.
Eg. There is a correlation between students'
study hours and their exam scores.
Logical hypothesis: This hypothesis assumes a
relationship between variables without collecting data
or evidence.(based on logic)
Eg. If a plant is deprived of sunlight, it is
expected that its growth will be negatively
affected compared to a plant that receives
adequate sunlight.

28. This Photo by Unknown Author is licensed under CC BY

29. To write a hypothesis:
Identify what the problem is.
Make an educated guess as to what direction of the
relationship or difference is.
Identify the major variables.
The format for writing a hypothesis is . . . o If (variables),
o Then (predict the outcome of the experiment using the
dependent variable).
Eg.Observation : Chocolate may cause acne.
scientific hypothesis statement that is measurable: If a
person’s frequency of acne is related to the amount of
chocolate a person consumes, then the frequency of acne
will be 25% higher when subjects consume large amounts
of chocolate (5 chocolate bars per day) than when subjects
consume little or no chocolate.

30. As a group, create hypothesis based
on sample observations/general
hypotheses.
A few sample items from which to develop scientific
hypothesis are:
1. Salt in soil may affect plant growth.
2. Temperature may cause leaves to change color.
3. Sunlight causes fruit to ripen more quickly.
4. Plant growth may be affected by the color of the
light.
5. Bacterial growth may be affected by temperature.
6. Ultra violet light may cause skin cancer.

31. Testing of hypothesis
Formulate a
Hypothesis
(Null and
Alternative
Hypotheses)
Choose a
Significance
Level (epresents
the probability of
making a Type I
error (rejecting
the null
hypothesis when
it's actually true)
Collect Data
(hypothesis and
research design)
Perform
Statistical
Analysis
Calculate Test
Statistic: (e.g., t-
statistic, z-score,
F-statistic).
Draw a
Conclusion
Consider
Limitations
(potential
sources of error,
and the
generalizability
of findings to
population)
Report Results
(research papers,
presentations, or
other appropriate
channels.)