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GNDU QUESTION PAPERS 2023
BA/BSc 6
th
SEMESTER
SOCIOLOGY
(Social Research and Scienc Methods)
Time Allowed: 3 Hours Maximum Marks: 100
Note: Aempt Five quesons in all, selecng at least One queson from each secon. The
Fih queson may be aempted from any secon. All quesons carry equal marks.
SECTION-A
1. Write a note on meaning and funcons of Social Research.
2. Discuss in detail the steps in the process of Social Research.
SECTION-B
3. What do you mean by Research Design? Explain in detail the types of Research Design.
4. What do you mean by Probability Sampling? Discuss its various types.
SECTION-C
5. What do you mean by Interview Schedule? Discuss the Advantages and Disadvantages
of Interview Schedule in Social Research.
6. Explain in detail Observaon and Case Study in Social Research.
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SECTION-D
7. Elaborate the various steps involved in report wring.
8. Discuss the role of coding and tabulaon in data analysis in Social Research.
GNDU ANSWER PAPERS 2023
BA/BSc 6
th
SEMESTER
SOCIOLOGY
(Social Research and Scienc Methods)
Time Allowed: 3 Hours Maximum Marks: 100
Note: Aempt Five quesons in all, selecng at least One queson from each secon. The
Fih queson may be aempted from any secon. All quesons carry equal marks.
SECTION-A
1. Write a note on meaning and funcons of Social Research.
Ans: Meaning of Social Research
Social research is the scientific study of human society, social relationships, and social
problems. It is a method of discovering new facts or verifying old facts about social life.
In simple words:
Social research means studying people and society in a planned, careful, and objective
way to understand how society works and how it can be improved.
For example:
• Why do some students drop out of school?
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• Does unemployment increase crime?
• How does poverty affect health?
• Do mobile phones affect children’s learning?
When researchers collect data (through surveys, interviews, observation, etc.) and analyze it
to find answers, they are doing social research.
So, social research is not random thinking—it follows a scientific process:
1. Identify a problem
2. Collect information
3. Analyze data
4. Draw conclusions
Because of this, social research is considered systematic, logical, and evidence-based.
Key Features of Social Research
Before understanding its functions, it helps to know what makes social research special:
• It studies human behavior and social relationships
• It uses scientific methods
• It is objective and unbiased
• It seeks truth and understanding
• It helps solve social problems
Functions of Social Research
Social research plays many important roles in society. These functions explain why it is
valuable for knowledge and social progress.
1. To Discover New Knowledge
One major function of social research is to discover new facts about society.
Society constantly changes—new technologies, lifestyles, cultures, and problems appear.
Social research helps us understand these new realities.
Example:
Research on social media has revealed:
• Its effect on mental health
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• Its role in spreading information
• Its influence on youth behavior
Without research, we would only rely on guesses or opinions.
So, social research expands our understanding of human life.
2. To Study Social Problems
Every society has problems—poverty, unemployment, crime, inequality, discrimination,
illiteracy, etc. Social research studies these problems deeply.
It helps answer questions like:
• What causes poverty?
• Why do crimes increase in cities?
• Why are some groups disadvantaged?
By understanding causes and patterns, solutions become possible.
Example:
Research showed that lack of education and unemployment increase crime rates. This
helped governments focus on education and employment programs.
Thus, social research helps society understand and address its problems.
3. To Test and Verify Existing Knowledge
Social research does not only discover new facts—it also checks whether old beliefs are true
or false.
Many social beliefs exist, such as:
• “Urban life is more stressful than rural life.”
• “Education reduces poverty.”
• “Joint families are more stable than nuclear families.”
Research tests these ideas with evidence.
Sometimes results confirm beliefs; sometimes they challenge them.
This process improves knowledge accuracy.
So, social research ensures knowledge is reliable and scientific.
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4. To Understand Social Behavior
Human behavior is complex. People act differently in different situations. Social research
studies patterns in behavior.
It helps answer:
• Why do people follow traditions?
• Why do teenagers rebel?
• Why do communities form groups?
• Why do social movements arise?
Understanding behavior helps predict and guide social change.
Example:
Research on voting behavior shows how caste, religion, education, and media influence
elections.
Thus, social research helps explain how people think and act in society.
5. To Help in Policy Making and Planning
Governments and organizations need accurate information to create policies. Social
research provides this data.
Policies on:
• Education
• Health
• Employment
• Women empowerment
• Rural development
are often based on research findings.
Example:
If research shows high malnutrition in rural children, government may start nutrition
programs.
Without research, policies would be based on assumptions and may fail.
So, social research supports effective governance and planning.
6. To Predict Social Trends
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Social research helps understand future social changes by studying present patterns.
It helps predict:
• Population growth
• Urbanization
• Migration
• Technology impact
• Changing family structures
Example:
Research predicted increasing urban migration in India, leading to city planning and
infrastructure development.
Thus, social research prepares society for future changes.
7. To Promote Social Welfare and Reform
Many social reforms have roots in social research. When problems are studied scientifically,
society becomes aware and reform movements begin.
Examples:
• Child labor studies → child protection laws
• Gender inequality research → women empowerment programs
• Caste discrimination research → social justice policies
Research exposes hidden issues and encourages social change.
So, social research contributes to social progress and justice.
8. To Develop Scientific Attitude
Social research encourages people to think scientifically rather than emotionally or blindly.
It promotes:
• Critical thinking
• Logical reasoning
• Evidence-based understanding
• Open-mindedness
This attitude is important for modern democratic societies.
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Instead of believing rumors or stereotypes, people learn to rely on facts.
Thus, social research develops rational and informed citizens.
9. To Support Academic Knowledge
Social research is the foundation of subjects like:
• Sociology
• Economics
• Political science
• Anthropology
• Social work
• Psychology
Students and scholars use research to build theories and knowledge.
Universities depend on research to expand understanding of society.
So, social research strengthens academic disciplines.
Importance of Social Research in Daily Life
Even common social improvements depend on research:
• Better education methods
• Public health campaigns
• Traffic safety rules
• Crime prevention strategies
• Digital awareness programs
All these come from studying human behavior and social patterns.
So, social research affects everyday life more than we realize.
Conclusion
Social research is the scientific study of society and human behavior. It seeks to understand
social relationships, discover facts, test beliefs, and solve social problems.
Its functions are wide and powerful—it generates knowledge, explains behavior, guides
policy, predicts trends, supports reforms, and promotes social welfare. Without social
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research, society would rely on assumptions, traditions, and guesses rather than facts and
understanding.
In simple terms, social research is like a mirror and a guide for society. It shows us what
society truly is and helps us decide what it should become. Through careful study and
evidence, it helps build a better, fairer, and more informed world.
2. Discuss in detail the steps in the process of Social Research.
Ans: Step 1: Identifying the Problem or Topic
Every research journey begins with a question. The researcher first identifies a problem or
topic worth studying. This could be anything from “Why do students prefer online
learning?” to “What factors influence voting behavior?”
At this stage, the researcher narrows down broad curiosity into a specific, researchable
problem. Without a clear problem, the rest of the process lacks direction.
Step 2: Review of Literature
Once the problem is identified, the next step is to see what others have already said about
it. This is called the review of literature. Researchers read books, articles, reports, and
previous studies to understand existing knowledge.
This step helps in two ways:
• It prevents duplication of work.
• It highlights gaps in knowledge that the new research can fill.
Step 3: Formulating Hypotheses
After reviewing literature, the researcher develops hypotheses—tentative explanations or
predictions. For example, if studying online learning, a hypothesis might be: “Students with
better internet access are more satisfied with online classes.”
Hypotheses give direction to the research. They act like guiding lights, suggesting what
relationships or patterns the researcher expects to find.
Step 4: Research Design
Now comes the planning stage. The researcher designs the study, deciding:
• What type of research to use (qualitative, quantitative, or mixed).
• What methods to apply (surveys, interviews, observations, experiments).
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• How to select participants (sampling techniques).
• What tools to use (questionnaires, interview guides, statistical software).
This step is crucial because a weak design leads to weak results. A strong design ensures
that the research is systematic and reliable.
Step 5: Data Collection
With the design ready, the researcher moves to data collection. This is where information is
gathered directly from the field. Methods vary:
• Surveys for large groups.
• Interviews for detailed insights.
• Observations for natural behavior.
• Secondary data from reports or archives.
Data collection must be careful and ethical. Respondents should feel respected, and their
privacy must be protected.
Step 6: Data Processing and Analysis
Raw data is like uncut stone—it needs shaping. The researcher organizes the data, often
coding responses, entering them into software, and cleaning errors.
Then comes analysis: applying statistical tests, thematic coding, or comparative methods to
uncover patterns. For example, analysis might show that students with stable internet
indeed report higher satisfaction.
This step transforms scattered information into meaningful findings.
Step 7: Interpretation of Results
Numbers and patterns alone don’t tell the full story. The researcher interprets the results,
connecting them back to the hypotheses and the broader social context.
Interpretation answers questions like:
• What do these findings mean?
• Do they support or reject the hypotheses?
• How do they compare with previous studies?
This step requires critical thinking, because results must be explained logically and linked to
real-world implications.
Step 8: Presentation of Findings
Finally, the researcher presents the findings in a clear, structured way—through reports,
articles, or presentations. This includes:
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• Introduction and background.
• Methods used.
• Results and analysis.
• Conclusions and recommendations.
Presentation ensures that knowledge is shared, not locked away. It allows others to learn,
critique, and build upon the research.
Step 9: Verification and Application
The process doesn’t end with presentation. Other scholars may verify the findings by
replicating the study. Policymakers, educators, or organizations may apply the results to
solve problems.
For example, if research shows that internet access improves online learning satisfaction,
governments might invest in better digital infrastructure.
Conclusion
So, the process of social research unfolds step by step:
1. Identify the problem.
2. Review literature.
3. Formulate hypotheses.
4. Design the research.
5. Collect data.
6. Process and analyze data.
7. Interpret results.
8. Present findings.
9. Verify and apply.
SECTION-B
3. What do you mean by Research Design? Explain in detail the types of Research Design.
Ans: What is Research Design? Meaning and Types of Research Design
Imagine you want to build a house. Before starting construction, you first create a plan or
blueprint—where the rooms will be, how strong the foundation should be, what materials
will be used, and how long it will take.
In the same way, when a researcher wants to study a social problem or topic, they first
prepare a clear plan about what to study, how to study, and why to study.
This plan is called Research Design.
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So in simple words:
Research Design is the overall plan or structure of a research study that guides the
researcher in collecting, analyzing, and interpreting data.
It tells the researcher:
• What data is needed
• From where it will be collected
• How it will be collected
• How it will be analyzed
• How conclusions will be drawn
Because of research design, research becomes systematic, organized, and scientific, not
random or confusing.
Definition of Research Design
Different scholars define research design in slightly different ways, but the meaning remains
the same.
• According to Kerlinger:
“Research design is the plan, structure, and strategy of investigation conceived to
obtain answers to research questions.”
• According to Kothari:
“Research design is the arrangement of conditions for collection and analysis of
data in a manner that aims to combine relevance with economy.”
In easy language:
Research design is the roadmap of research.
Why is Research Design Important?
Without research design, research is like traveling without a map—you may get lost or
waste time and money.
Research design helps in:
• Giving direction to research
• Saving time and cost
• Avoiding confusion
• Ensuring accuracy
• Making research scientific
• Helping achieve objectives
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So, research design is the foundation of good research.
Types of Research Design
Researchers use different types of research designs depending on their objective.
The main types are:
1. Exploratory Research Design
2. Descriptive Research Design
3. Experimental Research Design
4. Diagnostic Research Design
Let’s understand each in a simple and engaging way.
1. Exploratory Research Design
Imagine you hear that students in a college are stressed.
But you don’t know:
• Why they are stressed
• How many are stressed
• What causes stress
So first, you explore the situation by talking to students, observing them, reading reports,
etc.
This is exploratory research.
Exploratory Research Design is used when the problem is new, unclear, or not well
understood.
Its main aim is:
• To explore
• To discover ideas
• To understand the problem better
It does not give final answers but helps in forming hypotheses.
Methods used
• Interviews
• Case studies
• Observations
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• Literature review
• Focus groups
Example
A researcher wants to study why rural youth migrate to cities, but there is little information
available.
So he explores by interacting with migrants and communities.
2. Descriptive Research Design
Now imagine you already know that students are stressed.
But you want to know:
• How many students are stressed
• Which age group is most stressed
• What are common causes
Here you are describing the situation in detail.
Descriptive Research Design describes characteristics, facts, or conditions of a
population or phenomenon.
It answers:
• What is happening?
• Who is involved?
• Where?
• When?
• How much?
But it does not explain cause-effect relationships.
Methods used
• Surveys
• Questionnaires
• Observations
• Census
• Statistical data
Example
A survey showing:
• 60% college students feel exam stress
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• 40% face financial stress
• 30% face family pressure
This is descriptive research.
3. Experimental Research Design
Now suppose you want to know:
Does meditation reduce student stress?
So you divide students into two groups:
• Group A practices meditation
• Group B does not
Then you compare stress levels.
This is experimental research.
Experimental Research Design studies cause-and-effect relationships by controlling
variables.
The researcher changes one factor (independent variable) and observes its effect on
another (dependent variable).
Key features
• Control group
• Experimental group
• Manipulation of variables
• Measurement of effect
Example
Testing whether:
• New teaching method improves learning
• Exercise reduces obesity
• Counseling reduces anxiety
Experimental design is common in psychology, medicine, and education.
4. Diagnostic Research Design
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Now imagine you already know students are stressed and how many are stressed.
But you want to know:
What are the exact causes?
What solutions can help?
This is diagnostic research.
Diagnostic Research Design identifies causes of a problem and suggests solutions.
It goes deeper than descriptive research.
It answers:
• Why is the problem occurring?
• What factors are responsible?
• How can it be solved?
Example
A study finds:
• Stress is mainly due to exams, family expectations, and social media pressure
• Counseling and time-management training reduce stress
This is diagnostic research.
Comparison of Research Design Types
Let’s see the difference simply:
• Exploratory → explores problem
• Descriptive → describes situation
• Experimental → tests cause-effect
• Diagnostic → finds causes & solutions
So they are like stages:
Explore → Describe → Explain → Solve
How to Choose a Research Design?
A researcher chooses design based on:
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• Nature of problem
• Research objective
• Availability of data
• Time and cost
• Level of knowledge
Example:
If problem unknown → Exploratory
If facts needed → Descriptive
If cause-effect → Experimental
If solution needed → Diagnostic
Characteristics of a Good Research Design
A good research design should be:
• Clear
• Logical
• Flexible
• Practical
• Economical
• Accurate
• Reliable
It should help answer research questions effectively.
Conclusion
Research design is the backbone of any research study.
It is the careful plan that guides the researcher from beginning to end.
Without research design:
• Research becomes confusing
• Data becomes unreliable
• Conclusions become weak
There are four major types:
• Exploratory → for new problems
• Descriptive → for facts and description
• Experimental → for cause-effect testing
• Diagnostic → for causes and solutions
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Each type serves a different purpose, but all aim to make research systematic and
meaningful.
So, just like a blueprint helps build a strong house, research design helps build strong and
scientific research.
4. What do you mean by Probability Sampling? Discuss its various types.
Ans: What is Probability Sampling?
Imagine you want to study a large population—say, the opinions of college students in India
about online learning. It’s impossible to ask every single student. So, you take a sample—a
smaller group that represents the larger population.
Now, the big question is: How do you choose this sample so that it truly reflects the
population?
This is where probability sampling comes in. In probability sampling, every individual in the
population has a known, non-zero chance of being selected. That means the selection isn’t
based on guesswork or convenience—it’s based on randomization and fairness.
Because of this, probability sampling is considered more scientific and reliable. It reduces
bias and allows researchers to use statistical methods to generalize findings from the
sample to the whole population.
Types of Probability Sampling
There are several methods under probability sampling. Each has its own logic and use. Let’s
walk through them one by one.
1. Simple Random Sampling
This is the most straightforward method. Every individual in the population has an equal
chance of being selected.
Think of it like a lottery: if you put all student names in a box and draw 100 names
randomly, that’s simple random sampling.
Advantages:
• Easy to understand.
• Highly representative if the sample size is large.
Limitations:
• Requires a complete list of the population.
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• Not always practical for very large populations.
2. Systematic Sampling
Here, you select every kth individual from a list after choosing a random starting point.
For example, if you have a list of 1,000 students and you want a sample of 100, you could
select every 10th student after randomly picking a starting point.
Advantages:
• Simple and quick.
• Ensures even coverage across the population.
Limitations:
• If the list has hidden patterns (like students grouped by grades), it may introduce
bias.
3. Stratified Sampling
In stratified sampling, the population is divided into subgroups (called strata) based on
certain characteristics—like gender, age, or income. Then, random samples are taken from
each subgroup.
For example, if you want to study student opinions, you might divide them into strata based
on year of study (first-year, second-year, etc.) and then randomly select students from each
group.
Advantages:
• Ensures representation of all important subgroups.
• Improves accuracy of results.
Limitations:
• Requires detailed information about the population to create strata.
4. Cluster Sampling
Here, the population is divided into clusters (often based on geography or institutions), and
then entire clusters are randomly selected.
For example, instead of sampling individual students across India, you might randomly
select 10 universities and study all students within those universities.
Advantages:
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• Cost-effective and practical for large populations spread over wide areas.
• Easier to manage.
Limitations:
• Less precise than stratified sampling because clusters may not perfectly represent
the population.
5. Multistage Sampling
This is a combination of methods, often used for very large and complex populations.
For example, in the first stage, you might select states randomly. In the second stage, select
districts within those states. In the third stage, select schools within districts. Finally, select
students within schools.
Advantages:
• Flexible and practical for large-scale studies.
• Reduces cost and effort.
Limitations:
• More complex to design and analyze.
• Risk of sampling error at multiple stages.
Bringing It All Together
So, probability sampling is essentially about fairness and scientific accuracy. It ensures that
every individual has a chance of being included, which makes the sample more
representative of the population.
The main types—simple random, systematic, stratified, cluster, and multistage—are like
different tools in a toolbox. Researchers choose the right tool depending on the size of the
population, the information available, and the resources they have.
Conclusion
To sum up:
• Probability sampling means selecting samples in a way that gives everyone a known
chance of being chosen.
• It reduces bias and allows generalization of results.
• The main types are: simple random, systematic, stratified, cluster, and multistage
sampling.
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SECTION-C
5. What do you mean by Interview Schedule? Discuss the Advantages and Disadvantages
of Interview Schedule in Social Research.
Ans: Meaning of Interview Schedule in Social Research
Imagine a researcher wants to understand people’s opinions about education, health, or
village life. Instead of giving them a questionnaire to fill on their own, the researcher meets
them face-to-face, asks questions, and records their answers.
But the researcher cannot ask random questions — otherwise, every interview would be
different. So, they prepare a planned list of questions in advance, arranged in a proper
order. This prepared list is called an Interview Schedule.
In simple words:
An interview schedule is a structured list of questions used by a researcher to ask
respondents during a face-to-face interview and record their answers.
So, the key idea is:
• Questions are prepared beforehand
• The interviewer asks them directly
• Responses are recorded by the interviewer
It is different from a questionnaire because:
• Questionnaire → filled by respondent
• Interview Schedule → filled by interviewer
Definition (Exam-Ready)
An interview schedule is a systematic list of questions prepared by the researcher and used
during a personal interview to collect data from respondents in social research.
Example to Understand Easily
Suppose a researcher wants to study why students drop out of college.
If he uses a questionnaire:
• He sends forms to students
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• Students fill them themselves
If he uses an interview schedule:
• He meets each student personally
• Asks questions like:
o Why did you leave college?
o Financial problem?
o Family pressure?
o Lack of interest?
• He writes answers himself
This second method is interview schedule.
Advantages of Interview Schedule
Let’s now understand why researchers like this method. Think of it as benefits of talking
directly to people instead of giving forms.
1. Suitable for Illiterate or Less Educated People
In many societies, people cannot read or write properly. They cannot fill questionnaires.
But in an interview schedule:
• Researcher asks orally
• Respondent only speaks
• No reading/writing needed
So it works well in villages and rural studies.
Example: Farmers, laborers, elderly people.
2. More Accurate and Reliable Data
When respondents fill forms themselves, they may:
• Skip questions
• Misunderstand meaning
• Give incomplete answers
But in interviews:
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• Researcher explains questions
• Ensures all answers are given
• Clarifies confusion
So the data becomes more accurate.
3. Higher Response Rate
People often ignore questionnaires.
But when a researcher meets them personally:
• They feel respected
• They cooperate more
• They respond fully
So response rate becomes very high.
4. Possibility of Probing (Deep Information)
One of the biggest strengths of interviews is probing.
Probing means:
Asking extra questions to understand deeply.
Example:
Respondent: “I left school due to problems.”
Researcher: “What kind of problems?”
Respondent: “Financial.”
Researcher: “Income issue or fees issue?”
This deeper understanding is only possible in interviews.
5. Observation of Behavior and Emotions
In interview schedule, researcher sees respondent directly.
He can observe:
• Facial expressions
• Hesitation
• Confidence
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• Emotional reactions
This gives extra insight beyond words.
Example:
A person says “I am satisfied with life” but looks sad — researcher notices mismatch.
6. Suitable for Complex Questions
Some social research questions are complicated.
In interviews:
• Researcher explains
• Gives examples
• Rephrases
So even complex topics can be studied.
Disadvantages of Interview Schedule
Now let’s see why this method also has limitations. No method is perfect.
1. Very Time-Consuming
Interview schedule requires:
• Visiting each respondent
• Talking personally
• Recording answers
So it takes much more time than questionnaires.
Example:
Questionnaire → 200 responses in 1 day
Interview → 200 responses may take weeks
2. Costly Method
Because of travel, time, and manpower, interview schedules are expensive.
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Costs include:
• Travel expenses
• Interviewer salary
• Training cost
So large-scale studies become costly.
3. Interviewer Bias
Sometimes interviewer may influence responses.
Example:
If interviewer shows approval or disapproval:
• Respondent may change answer
• Try to please interviewer
So data may become biased.
4. Lack of Anonymity
In questionnaires, identity may remain hidden.
But in interviews:
• Researcher knows respondent
• Respondent may hesitate
Especially for sensitive topics:
• Income
• Crime
• Personal problems
• Sexual behavior
People may hide truth.
5. Requires Skilled Interviewers
Interview schedule is not easy to conduct.
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Interviewer must know:
• How to ask neutrally
• How to probe
• How to record correctly
• How to build trust
Untrained interviewer can spoil data.
6. Limited Coverage
Because of time and cost, researcher can interview only limited people.
So:
• Sample size becomes smaller
• Generalization becomes weaker
Simple Comparison: Interview Schedule vs Questionnaire
Basis
Interview Schedule
Questionnaire
Who fills
Interviewer
Respondent
Contact
Face-to-face
Indirect
Literacy needed
No
Yes
Cost
High
Low
Response rate
High
Low
Depth
High
Low
Conclusion
An interview schedule is a structured list of questions used by researchers during personal
interviews to collect information in social research. It is one of the most effective methods
for gathering detailed, reliable, and meaningful data, especially among illiterate or rural
populations.
Its major strengths are:
• Accuracy
• Depth
• Personal interaction
• High response rate
However, it also has limitations such as:
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• High cost
• Time consumption
• Interviewer bias
• Limited coverage
So, researchers choose interview schedules when they need deep, accurate, and personal
data, and they use questionnaires when they need large-scale, quick, and economical data.
6. Explain in detail Observaon and Case Study in Social Research.
Ans: Observation in Social Research
Observation is one of the oldest and most natural methods of research. At its core, it means
watching people, events, or situations carefully to gather information. Unlike surveys or
interviews, where people tell you what they think or do, observation lets you see it directly.
Types of Observation
1. Participant Observation
o Here, the researcher becomes part of the group being studied.
o For example, if you want to study classroom behavior, you might sit in the
class as a student and observe interactions.
o Advantage: You get insider knowledge.
o Limitation: Risk of bias because you’re part of the group.
2. Non-Participant Observation
o The researcher observes without joining the group.
o Example: Watching how customers behave in a supermarket from a distance.
o Advantage: More objective.
o Limitation: You may miss deeper insights since you’re not involved.
3. Structured Observation
o The researcher uses a checklist or framework to record specific behaviors.
o Example: Counting how many times students raise their hands in class.
o Advantage: Data is systematic and easy to analyze.
o Limitation: May miss unexpected behaviors.
4. Unstructured Observation
o The researcher observes freely without a fixed plan.
o Example: Spending time in a village and noting down everyday life.
o Advantage: Rich, detailed insights.
o Limitation: Harder to analyze statistically.
Strengths of Observation
• Provides direct evidence of behavior.
• Useful when people may not accurately report their actions.
• Helps capture natural, real-life situations.
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Weaknesses of Observation
• Time-consuming.
• Observer bias may affect results.
• Some behaviors are hidden and cannot be observed directly.
Case Study in Social Research
A case study is an in-depth investigation of a single unit—this could be a person, a group, an
institution, or even an event. Instead of looking at large numbers, case studies dive deep
into one subject to understand it thoroughly.
Features of Case Studies
• Focus on one case at a time.
• Use multiple sources of data (interviews, documents, observation).
• Provide detailed, holistic understanding.
Example
Suppose a researcher wants to study the impact of unemployment on family life. Instead of
surveying thousands of families, they might select one family and study them closely over
time—interviewing members, observing routines, and analyzing documents.
Types of Case Studies
1. Explanatory Case Study
o Explains why something happens.
o Example: Studying why a particular school succeeded in reducing dropout
rates.
2. Descriptive Case Study
o Describes a situation in detail.
o Example: Documenting the lifestyle of a tribal community.
3. Exploratory Case Study
o Used when little is known about a topic.
o Example: Exploring how young people use social media in rural areas.
Strengths of Case Studies
• Provide rich, detailed insights.
• Useful for exploring new areas of research.
• Can reveal complex relationships and processes.
Weaknesses of Case Studies
• Findings may not be generalizable to larger populations.
• Risk of researcher bias.
• Time-intensive.
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Observation vs. Case Study
While both are qualitative methods, they differ in focus:
• Observation is about watching behavior directly, often across multiple people or
settings.
• Case Study is about deeply analyzing one unit in detail, often combining observation
with other methods.
Together, they complement each other. For example, a researcher studying classroom
dynamics might use observation to watch general behavior and then conduct a case study
of one particular student to understand their personal experience.
Conclusion
In social research, Observation and Case Study are powerful tools. Observation lets
researchers see behavior as it happens, while case studies allow them to dive deep into one
subject for a holistic understanding. Both methods have strengths and limitations, but when
used carefully, they provide insights that surveys or experiments alone cannot capture.
SECTION-D
7. Elaborate the various steps involved in report wring.
Ans: Steps Involved in Report Writing
1. Understanding the Purpose of the Report
Before writing anything, the first step is to clearly understand why the report is being
written. Every report has a goal. For example:
• To present research findings
• To analyze a problem
• To evaluate a project
• To suggest solutions
If you do not know the purpose, your writing may become confusing or irrelevant. So always
ask yourself:
What is the main objective of this report?
Who will read it?
Understanding the audience (teacher, researcher, organization, or public) also helps decide
the language and detail level.
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2. Planning and Organizing Information
Once the purpose is clear, the next step is planning what information to include and how to
arrange it. This stage is like creating a roadmap before starting a journey.
Here you decide:
• What topics will be covered
• What data or evidence will be used
• What order will be followed
Most reports follow a standard structure such as:
• Introduction
• Methodology
• Results
• Discussion
• Conclusion
Planning prevents repetition and keeps the report logical and smooth.
3. Collecting and Verifying Information
A report must be based on accurate and reliable information. So before writing, gather all
relevant material such as:
• Research data
• Survey results
• Books and articles
• Observations
• Statistics
After collecting, verify the facts. Check if data is correct, sources are reliable, and
information is complete. Incorrect data can make the entire report weak.
This step ensures your report is trustworthy and credible.
4. Creating an Outline (Report Framework)
An outline is like the skeleton of the report. It shows the headings and subheadings in order.
For example:
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1. Introduction
2. Objectives
3. Methodology
4. Findings
5. Discussion
6. Conclusion
7. Recommendations
Making an outline has many benefits:
• Keeps writing focused
• Ensures logical flow
• Saves time
• Avoids missing points
Professional writers always create outlines before drafting.
5. Writing the First Draft
Now comes the actual writing stage. At this step, do not worry too much about perfection.
The aim is to put all ideas into words according to the outline.
Each section has its own role:
Introduction
Explains the topic, background, and purpose.
Methodology
Describes how research was conducted.
Findings/Results
Presents data and observations.
Discussion
Interprets meaning of results.
Conclusion
Summarizes main points.
Recommendations
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Suggests actions or solutions.
Write clearly, simply, and objectively. Reports should be factual rather than emotional.
6. Revising and Editing the Report
The first draft is never final. Good reports are improved through revision. This step includes:
• Checking clarity
• Removing repetition
• Improving sentence structure
• Ensuring logical flow
• Correcting grammar
Ask yourself:
Does the report answer the research question?
Are ideas clear and connected?
Is language simple and formal?
Revision transforms a rough draft into a polished document.
7. Checking Format and Presentation
A report is not only judged by content but also by presentation. Proper formatting makes
reading easy and professional.
Check:
• Headings and subheadings
• Page numbering
• Tables and charts labeling
• Margins and spacing
• Font consistency
Also include essential parts like:
• Title page
• Table of contents
• References
• Appendices
Neat presentation creates a strong impression.
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8. Proofreading the Final Report
Proofreading is the last quality check before submission. It focuses on small errors such as:
• Spelling mistakes
• Grammar errors
• Typing errors
• Punctuation issues
Even a good report can lose marks due to careless mistakes. So read slowly and carefully, or
read aloud to catch errors.
9. Writing References and Citations
If you used books, articles, websites, or data sources, you must acknowledge them. This step
avoids plagiarism and shows academic honesty.
Common citation styles include:
• APA
• MLA
• Chicago
References strengthen credibility and allow readers to verify information.
Final Understanding: Report Writing as a Process
We can understand report writing like building a house:
• Purpose = foundation
• Planning = design
• Information = materials
• Draft = construction
• Revision = finishing
• Proofreading = inspection
If any step is skipped, the report becomes weak or unclear.
Conclusion
Report writing is not just about writing facts; it is a systematic process of organizing
knowledge in a clear, logical, and meaningful way. The main steps involved include
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understanding the purpose, planning content, collecting data, creating an outline, drafting,
revising, formatting, proofreading, and citing sources. Each step plays an important role in
making the report accurate, readable, and professional.
8. Discuss the role of coding and tabulaon in data analysis in Social Research.
Ans: Coding in Social Research
When researchers collect data—whether through surveys, interviews, or observations—the
information often comes in raw form. For example, answers might be long sentences, open-
ended responses, or varied categories. To make sense of this, researchers use coding.
What is Coding?
Coding means classifying and assigning symbols or numbers to responses so they can be
systematically analyzed. It’s like turning messy notes into a structured spreadsheet.
For instance:
• If you ask 100 people about their favorite mode of transport, you might get answers
like “bus,” “train,” “car,” “bike.”
• Coding would assign numbers: bus = 1, train = 2, car = 3, bike = 4.
• Now, instead of handling words, you can handle numbers, which makes analysis
easier.
Types of Coding
1. Open Coding
o Used in qualitative research.
o Researchers read responses and identify themes or categories.
o Example: In interviews about online learning, codes might be “flexibility,”
“technical issues,” “teacher support.”
2. Closed Coding
o Used in quantitative research.
o Predefined categories are given, and responses are slotted into them.
o Example: A survey with multiple-choice answers already provides coded
options.
3. Manual vs. Computer Coding
o Manual coding involves researchers themselves categorizing responses.
o Computer coding uses software to automate the process, especially for large
datasets.
Importance of Coding
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• It simplifies complex data.
• It allows statistical analysis.
• It ensures consistency in handling responses.
• It bridges qualitative insights with quantitative measurement.
Tabulation in Social Research
Once data is coded, the next step is tabulation. This means arranging data into tables so
patterns become visible.
What is Tabulation?
Tabulation is the process of systematically presenting data in rows and columns. It
transforms coded numbers into organized tables that highlight frequencies, percentages,
and relationships.
For example, after coding transport preferences, you might create a table like this:
Mode of Transport
Frequency
Percentage
Bus
40
40%
Train
25
25%
Car
20
20%
Bike
15
15%
This table immediately shows the distribution of preferences.
Types of Tabulation
1. Simple Tabulation
o Presents one characteristic at a time.
o Example: Number of students preferring each transport mode.
2. Complex Tabulation
o Shows relationships between two or more variables.
o Example: Transport preference by gender.
Gender
Bus
Train
Car
Bike
Male
20
15
10
5
Female
20
10
10
10
This reveals deeper insights, like whether men and women differ in transport choices.
Role of Coding and Tabulation in Data Analysis
Together, coding and tabulation play a crucial role in transforming raw data into meaningful
knowledge:
1. Organization
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o Coding organizes responses into categories.
o Tabulation arranges those categories into clear tables.
2. Simplification
o Complex, scattered data becomes manageable.
o Researchers can quickly see frequencies and percentages.
3. Comparison
o Tabulation allows comparison across groups, variables, or time periods.
4. Foundation for Statistical Analysis
o Once data is coded and tabulated, researchers can apply statistical tests (like
correlation, regression, chi-square).
o Without coding and tabulation, these tests would be impossible.
5. Clarity in Presentation
o Tables make findings easy to present in reports, articles, or policy documents.
o They provide a visual summary that readers can grasp quickly.
Example Narrative
Imagine you’re studying the impact of social media on students. You collect responses from
200 students. Some say it helps them learn, others say it distracts them, and some mention
both.
• Step 1: Coding You assign codes: “helps learning = 1,” “distracts = 2,” “both = 3.”
Now you can count how many students fall into each category.
• Step 2: Tabulation You create a table showing frequencies and percentages. Maybe
80 students said “helps learning,” 70 said “distracts,” and 50 said “both.”
From this, you can easily see the distribution and later analyze whether factors like age or
gender influence these opinions.
Conclusion
In social research, coding and tabulation are the backbone of data analysis. Coding
transforms raw responses into structured categories, while tabulation arranges those
categories into tables that reveal patterns and relationships. Together, they make data
understandable, comparable, and ready for deeper statistical exploration.
“This paper has been carefully prepared for educaonal purposes. If you noce any
mistakes or have suggesons, feel free to share your feedback.”
