1. Define the term "research" characteristics of a specific group, situation, or phenomenon.

Research is a structured and systematic process of studying a For example, a company might conduct a survey to
particular topic or problem to discover new facts, reach understand customer preferences, shopping habits, or
conclusions, or create solutions. It involves defining a clear demographic details. This type of research is often used to
objective, collecting relevant data, analyzing that data using answer “what,” “when,” “where,” and “how” questions.
scientific methods, and interpreting the results to gain deeper Exploratory research is used when there is little existing
insights. In simple terms, research helps us answer questions or information about a topic. It helps researchers explore ideas,
solve problems by investigating things carefully and logically gain insights, and develop a better understanding of
rather than guessing or assuming. unfamiliar problems. It is flexible and open-ended, often
2. State two key objectives of conducting business research using interviews or focus groups to generate new ideas or
One major objective of business research is to support effective clarify vague issues.
decision-making. Businesses operate in dynamic environments 4. What is applied research?
and face constant challenges, such as changing customer needs or Applied research is a type of research that focuses on solving
new market trends. Through research, companies can gather real-world problems or addressing specific practical issues.
reliable information that helps them make smart choices—like Unlike basic research, which aims to increase general
launching a new product, entering a new market, or improving knowledge, applied research is more action-oriented. For
customer service. example, a business may use applied research to find out
Another key objective is to identify and solve business problems. why customers are leaving their services and then take steps
For example, if sales are dropping or employee satisfaction is low, to improve retention. It is commonly used in business,
research helps diagnose the root cause of these issues. Once the medicine, engineering, and education to develop solutions
problem is understood, businesses can take targeted actions to that can be immediately implemented.
resolve it and improve performance. 5. Define research design in simple terms
3. Mention any two types of research Research design is like a blueprint or plan for how a research
Descriptive research is used when we want to describe the
project will be carried out. It outlines what will be studied, how 8. State the purpose of framing a null hypothesis in research
data will be collected, what methods will be used to analyze it, The null hypothesis is a statement that there is no effect or no
and how the results will be interpreted. A good research design relationship between variables in a study. It acts as a starting
ensures that the study is organized, efficient, and focused on point for statistical testing. The purpose of framing a null
achieving its objective. In simple words, it is the structure that hypothesis is to provide a benchmark for comparison.
guides the entire research process from start to finish. Researchers then test this hypothesis using data to either accept
6. List any two features of a good research design or reject it. If the null hypothesis is rejected, it suggests that
First, a good research design ensures reliability and accuracy. there is a statistically significant result, meaning the observed
This means the research methods and tools used should effect is likely not due to chance. This helps in making objective
produce consistent and dependable results every time the and evidence-based conclusions.
study is repeated. 9. Differentiate between sampling error and non-sampling
Second, it should be economical and efficient. A good design error
makes the best use of time, money, and resources while still Sampling error occurs when the sample chosen for a study does
achieving high-quality outcomes. It avoids unnecessary steps not perfectly represent the entire population. This happens due
and keeps the research process practical and cost-effective. to chance variations in the selection process and is usually
7. What is meant by exploratory research design? measurable. For example, if you survey only 100 people out of
Exploratory research design is used at the early stages of 10,000, the results may not fully reflect the opinions of
research when the problem is not clearly defined. It helps everyone.
researchers gain a deeper understanding of an issue, generate Non-sampling error, on the other hand, refers to mistakes that
new ideas, or form hypotheses. This type of design is flexible occur during the data collection or processing stage. These can
and often qualitative, using interviews, case studies, or open- include errors like incorrect questionnaire design, interviewer
ended surveys. It does not aim to provide final answers but bias, recording mistakes, or respondents giving false answers.
instead prepares the ground for more detailed and structured Non-sampling errors are often harder to detect and control
research later on. compared to sampling errors.
11. List two key problems associated with measurement in ━━━━━━━━━━━━━━━━━━━━━━
management research 13. Mention any two uses of rating scales in business
━━━━━━━━━━━━━━━━━━━━━━ research
One key problem is subjectivity in responses. In management ━━━━━━━━━━━━━━━━━━━━━━
research, many variables—like employee satisfaction or First, rating scales are used to measure customer satisfaction.
leadership quality—are abstract and depend on personal For example, after a service experience, customers might be
opinions, which can vary widely. This makes it difficult to ensure asked to rate their satisfaction from 1 to 5. This helps
accuracy in measurement. businesses understand how well they are performing.
Another issue is inconsistency in measurement tools. If the same Second, they are useful in employee performance evaluation.
concept is measured using different methods across studies or Supervisors can use rating scales to assess employees on
even within the same study, the results may not be comparable various parameters like teamwork, punctuality, or
or reliable. For instance, a poorly designed questionnaire can lead communication skills, allowing for consistent and fair
to misleading data. evaluations.
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12. What is a Semantic Differential Scale? ━━━━━━━━━━━━━━━━━━━━━━
━━━━━━━━━━━━━━━━━━━━━━ 14. Define a nominal scale with an example
A Semantic Differential Scale is a type of rating scale used to ━━━━━━━━━━━━━━━━━━━━━━
measure people’s attitudes or feelings about a concept, object, or A nominal scale is the simplest type of measurement scale,
event. It presents respondents with pairs of opposite adjectives— where data is categorized without any order or ranking. It is
such as “Happy – Unhappy” or “Efficient – Inefficient”—and asks used to label variables with names or categories. For
them to choose a point along a scale between the two. This helps example, departments in a company—such as HR, Marketing,
capture the intensity and direction of a person’s attitude. It’s Sales, and Finance—can be classified using a nominal scale.
widely used in marketing and brand perception studies. Each category is different, but there is no implied hierarchy or
value difference among them.
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15. What is an independent variable in experimental 17. What is hypothesis formulation in the research process?
research? ━━━━━━━━━━━━━━━━━━━━━━
━━━━━━━━━━━━━━━━━━━━━━ Hypothesis formulation is the step in research where a testable
An independent variable is the one that the researcher statement or prediction is made about the relationship between two
manipulates or controls in an experiment to observe its or more variables. It provides direction to the study and sets a clear
effect on another variable. It is considered the “cause” in focus for data collection and analysis. For example, a researcher may
a cause-and-effect relationship. For example, in a study hypothesize that “higher employee motivation leads to better job
measuring the impact of training hours on employee performance.” This hypothesis can then be tested using data to
productivity, the number of training hours is the support or reject the claim.
independent variable, as it is being changed to see its ━━━━━━━━━━━━━━━━━━━━━━
effect on productivity. 18. Define validity in the context of measurement in management
16. Give one example each of a control group and a research
treatment group ━━━━━━━━━━━━━━━━━━━━━━
━━━━━━━━━━━━━━━━━━━━━━ Validity refers to how accurately a tool or method measures what it is
A control group is the group that does not receive the intended to measure. In management research, if a questionnaire is
experimental treatment and is used for comparison. For designed to assess employee engagement, it should actually measure
example, in a study on a new sales training method, the that specific concept and not something else like job satisfaction or
employees who continue with the old training program motivation. High validity ensures that the results of the research truly
form the control group. reflect the variable being studied, leading to more trustworthy
The treatment group is the one that receives the new conclusions.
intervention. In this case, the employees who undergo
the new sales training program are part of the treatment
group. The difference in outcomes between the two
groups shows the effect of the new method.
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━━━━━━━━━━━━━━━━━━━━━━ 21. Define exploratory research
19. Define the term 'statistical population' with one example ━━━━━━━━━━━━━━━━━━━━━━
━━━━━━━━━━━━━━━━━━━━━━ Exploratory research is a type of research that is used when the
A statistical population refers to the entire group of individuals, problem is not well understood or clearly defined. Its main
items, or data that a researcher wants to study or draw purpose is to explore the topic, gather preliminary information,
conclusions about. It forms the base from which a sample is and identify patterns, ideas, or insights. It is usually flexible and
selected. For example, if a company wants to study customer open-ended, allowing the researcher to look at various angles.
satisfaction, the statistical population would be all customers This type of research often leads to the development of clearer
who purchased from the company in the last year. hypotheses or questions for future studies and is commonly
━━━━━━━━━━━━━━━━━━━━━━ used at the initial stage of a research project.
20. Define data editing in the context of data analysis ━━━━━━━━━━━━━━━━━━━━━━
━━━━━━━━━━━━━━━━━━━━━━ 22. Write two characteristics of a good research problem
Data editing is the process of reviewing and cleaning collected ━━━━━━━━━━━━━━━━━━━━━━
data to ensure its accuracy, completeness, and consistency First, a good research problem should be clear and specific. It
before analysis. It involves correcting errors, dealing with should be stated in a way that leaves no confusion about what
missing values, and checking for inconsistencies in responses. is being studied, so that the researcher can focus their efforts
This step is crucial because poor-quality data can lead to effectively.
incorrect analysis and misleading results. For example, if a Second, it should be researchable. This means there must be
respondent skips a question or enters conflicting answers, enough data or methods available to investigate the problem. A
those issues must be addressed during editing. good research problem can be studied through observation,
surveys, or analysis, and should lead to meaningful findings.
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23. What is meant by a research question?
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A research question is a clear, focused, and concise question . This outlines how the research will be conducted, including
that a research study aims to answer. It serves as the the research design, data collection methods, sample selection,
foundation of the entire research process. For example, a and tools for analysis. It helps reviewers understand how the
research question could be: “How does remote working affect research will be carried out and whether it is practical and
employee productivity in marketing firms?” A well-framed reliable
research question helps guide the direction of the study, data 26. Differentiate between cross-sectional and longitudinal
collection, and analysis, ensuring that the research remains on research
track. Cross-sectional research involves studying a population or a
━━━━━━━━━━━━━━━━━━━━━━ sample at a single point in time. It gives a snapshot of the current
24. What do you mean by a questionnaire? situation. For example, a company may survey customer
A questionnaire is a set of written questions used to collect satisfaction once in March and analyze the results.
information from people. It is one of the most common tools Longitudinal research, on the other hand, involves studying the
for gathering data in research, especially in surveys. same group over a period of time—weeks, months, or even years
Questionnaires can include open-ended questions (where —to observe changes or trends. For example, tracking employee
people write their own answers) or close-ended questions (like engagement every quarter for two years is a longitudinal study.
multiple choice or ratings). They are often used in business 27. Name any two qualitative techniques used in exploratory
research to understand customer preferences, employee research
feedback, or market trends. ━━━━━━━━━━━━━━━━━━━━━━ One qualitative technique is in-depth interviews. These are one-
25. State two components of a research proposal on-one conversations between a researcher and a participant that
One key component is the introduction, which explains the help uncover deep insights, feelings, and motivations.
background of the study, the research problem, and its Another technique is focus group discussions. In this method, a
significance. It sets the stage for why the research is important. small group of people discusses a topic guided by a moderator. It
Another important component is the methodology section is useful for exploring opinions and perceptions in a group setting.
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28. What is the difference between ordinal and interval scales? 30. List any two differences between a bar chart and a
━━━━━━━━━━━━━━━━━━━━━━ histogram
An ordinal scale ranks data in a specific order, but the ━━━━━━━━━━━━━━━━━━━━━━
difference between the values is not measurable. For example, A bar chart is used to display and compare discrete categories
a customer satisfaction survey that uses rankings like “Poor,” or groups (like different departments or product types). In a bar
“Average,” “Good,” and “Excellent” shows order but not the chart, the bars are separated by spaces.
exact difference between them. A histogram, on the other hand, is used to show the distribution
An interval scale not only shows order but also measures the of continuous data (like age or income). In histograms, the bars
exact distance between values. A good example is temperature touch each other to indicate that the data is continuous and
in Celsius—30°C is exactly 10 degrees warmer than 20°C, and grouped into intervals.
the difference is meaningful and consistent.
━━━━━━━━━━━━━━━━━━━━━━ 1. Explain the steps involved in coding and tabulating raw
29. List any two characteristics of a good sample data for statistical analysis.
━━━━━━━━━━━━━━━━━━━━━━ Coding and Tabulating Raw Data – Explained in Detail:
First, a good sample should be representative of the When researchers collect data from surveys, interviews, or
population. This means it should accurately reflect the observations, the data is usually in a raw and unstructured
characteristics of the whole group so that conclusions drawn format. To analyze it meaningfully using statistical tools, the
from the sample can apply to the population. data needs to be organized through a process called coding and
Second, it should be adequate in size. A sample that is too small tabulation. Here’s how each step works:
may lead to biased results, while a sufficiently large sample
improves accuracy and confidence in the research findings.
Step 1: Data Cleaning and Preparation Step 4: Tabulating the Data
Before coding begins, it’s important to check the raw data for After the data is coded and entered, tabulation involves
any errors or inconsistencies. This involves identifying summarizing it into tables. These tables can show the frequency
incomplete responses, duplicates, or unclear answers. Cleaning (how often each answer was chosen), percentages, averages, or
the data ensures that only valid and usable information is other relevant summaries. Tabulation helps researchers see
included for analysis. trends and relationships among variables. For example, a
Step 2: Coding the Data frequency table might show that 40% of customers were "very
Coding is the process of assigning numerical or symbolic values satisfied" while only 10% were "dissatisfied."
to responses, especially for qualitative data (like text-based Step 5: Interpreting the Tables
answers). For example, if a survey asks “How satisfied are you The final step is interpreting the tabulated results. Researchers
with our service?” and provides answers like “Very satisfied,” examine the tables to identify patterns, make comparisons, and
“Satisfied,” “Neutral,” “Dissatisfied,” and “Very dissatisfied,” draw conclusions. For example, if most customers who gave a
these can be coded as 5, 4, 3, 2, and 1 respectively. This makes satisfaction rating of 4 or 5 also mentioned “quick service” in
it easier to enter and analyze the data using software. Open- their comments, it suggests that service speed is a key driver of
ended responses (e.g., comments or suggestions) are grouped satisfaction.
into categories based on common themes and then given a In summary, coding and tabulating help convert messy raw data
code number. This step transforms verbal or written feedback into a structured, understandable format that can be analyzed
into measurable data. statistically to generate insights and make informed decisions.
Step 3: Entering the Data 2.Practical Steps to Determine an Appropriate Sampling Frame
Once all responses are coded, they are entered into a data in a Research Study on Customer Satisfaction in Retail..
management system like Microsoft Excel, SPSS, or Google In a research study on customer satisfaction, choosing the right
Sheets. Each row usually represents a respondent, and each sampling frame is extremely important because it directly
column represents a question or variable. Accuracy during this affects the accuracy and reliability of your findings. A sampling
step is crucial to avoid errors in the final analysis. frame is the actual list of people from which you select your
sample.
To make sure your research targets the right group of Step 4: Clean and Organize the Data
customers, you need to follow a series of practical steps to Before using the data, it must be cleaned. Remove duplicate
build a good sampling frame. Here’s how it works: entries, correct spelling mistakes, eliminate outdated records
Step 1: Clearly Define the Target Population (e.g., phone numbers or emails that no longer work), and verify
Start by defining exactly who you want to study. In the context any suspicious information. The goal is to have a clean, complete,
of customer satisfaction in retail, your target population could and organized list of customers.
be "all customers who made a purchase from the store in the Step 5: Confirm the Sampling Frame Matches the Target
last three months" or "loyalty card members who shopped Population
more than twice this year." The definition should be specific After organizing the data, double-check that it reflects your
and relevant to your research goals. originally defined population. For example, if your population was
Step 2: Identify Possible Sources of Customer Information "customers from the last three months," ensure that everyone in
Next, identify where you can find reliable information about the list matches that timeline. This step helps avoid mismatches
these customers. Common sources in retail include billing or between your sampling frame and your actual research goals.
transaction records, customer loyalty programs, online order Step 6: Choose a Sampling Method
databases, email subscriber lists, or membership apps. These Once the sampling frame is finalized, you can now choose how to
sources contain customer contact details and purchase select the sample from it. This could be done using simple random
history, which help create your sampling frame. sampling, systematic sampling, or stratified sampling, depending
Step 3: Evaluate the Quality of the Data Source on your research design. The better your sampling frame, the
Now, check whether the chosen data source is accurate and more accurate and representative your sample will be.
complete. Does it cover all types of customers—online and in- In summary, determining a proper sampling frame involves
store? Are the customer details up-to-date? Is anyone defining your population, finding reliable customer data sources,
missing, like walk-in customers who don’t register their cleaning and verifying the data, and ensuring it matches your
contact info? This step ensures your sampling frame is fair and research goal. A well-prepared sampling frame helps in collecting
not biased toward one group. accurate and unbiased information, which leads to trustworthy
conclusions about customer satisfaction.
What is meant by ‘sampling frame’? leading to biased results and inaccurate conclusions. For
Definition: example, if a researcher wants to study opinions of university
A sampling frame is a complete and accurate list of all the units students but the sampling frame only includes students from
(people, households, organizations, etc.) in the population from certain faculties, it may exclude others who are also part of the
which a researcher intends to select a sample. population.
Purpose: 2. Accuracy: Accuracy refers to the correctness and up-to-
The sampling frame serves as the practical representation of dateness of the information contained in the sampling frame.
the target population. Since researchers often cannot access All names, contact details, and other relevant data should
the entire population, they use the sampling frame to select a reflect the current status of each individual or unit in the
subset (sample) that can provide insights about the whole. population. Inaccurate information can lead to difficulties in
Example: contacting respondents or in misclassifying them, which affects
Suppose a researcher wants to study the opinions of university the quality and reliability of the collected data. For instance,
students at a particular institution. using a year-old mailing list might result in contacting people
•Target population: All currently enrolled students at the who have moved away or are no longer part of the population.
university. 3. Non-duplication :Each unit or member in a sampling frame
•Sampling frame: The university’s current student enrollment should appear only once. Duplication can result in
database or list. overrepresentation of certain individuals or groups, thereby
•Characteristics: distorting the sample and introducing bias. This characteristic
1.Completeness : A good sampling frame must be complete, ensures that every element has an equal and fair chance of
meaning it should include every unit or member of the target selection. If the same person is listed multiple times—perhaps
population. This ensures that all individuals have a chance of because they registered more than once or used different
being selected for the sample, which is essential for achieving names—they may be more likely to be selected, which
representativeness. Incomplete sampling frames can result in undermines the integrity of the sampling process.
undercoverage, where certain groups are left out entirely,
4. Accessibility :A sampling frame should consist of elements various situations—and asking them to tell a story about
that are accessible or reachable by the researcher using the what they see. The researcher prompts them to explain what
chosen method of contact. Whether the study is conducted is happening in the picture, what led up to it, what the
through phone calls, emails, postal mail, or in-person visits, the characters are thinking or feeling, and what the outcome
contact details provided must be valid and usable. If selected might be.
units cannot be contacted due to outdated or incorrect Purpose:
information, the response rate may decrease, and the findings This method helps uncover the participant’s underlying
could be biased. For example, an email survey would be attitudes, emotions, and beliefs by projecting their own
ineffective if many addresses in the sampling frame are invalid experiences and perceptions onto the image.
or inactive. The following are just a few of the ways the TAT is often
5. Relevance : Relevance means that the sampling frame utilized:
includes only those individuals or units that truly belong to the •To learn more about a person. Psychologists might use
target population. Including irrelevant entries (a problem this test as they are getting to know more about a client. The
known as overcoverage) can dilute the quality of the data and test acts as an icebreaker while providing helpful
may lead to misleading results. A relevant sampling frame information about potential emotional conflicts the client
ensures that every entry aligns with the purpose of the may have. The way the person builds the story and responds
research. For example, if the study is about public school to characters or situations similar to themselves and their
teachers, the sampling frame should not include private school experiences gives the person conducting the test insight into
staff or administrative personnel who do not fit the target the person's internal world.
criteria. •To help people express their feelings. The TAT is often
4.Describe any two projective techniques used in qualitative used as a therapeutic tool for clients to express feelings non-
research. directly. Sharing feelings is hard, and a person might not yet
1. Thematic Apperception Test (TAT) The Thematic feel ready to face these complicated emotions head-on. What
Apperception Test involves showing participants ambiguous they can do, thanks to the TAT, is identify the emotion when
images—usually of people in viewed from an outside perspective.
•To explore themes related to the person's life 2. Word Association Test
experiences. It's normal for people to interpret the card In a word association test, participants are presented with a list of
scenes in relation to their own experiences. So, when words (stimulus words) and are asked to respond with the first word
people are dealing with difficult life experiences—like job that comes to their mind. The idea is that the immediate word they
loss, divorce, or health issues—they might see their own associate reveals subconscious connections or emotional responses
lives reflected in those scenes. This can help them explore to the stimulus.
these issues in greater depth throughout therapy. Purpose: This technique helps identify how people perceive brands,
•To assess someone for psychological conditions. The concepts, or ideas at an instinctive level. It’s useful in understanding
test is sometimes used as a tool to assess for emotional triggers and brand associations.
personality disorders or thought disorders.4 Details of the Word Association Test
•To evaluate crime suspects. Clinicians may administer •The test comprises 60 words that are projected on a screen for
the test to criminals to assess the risk of recidivism or to 15 seconds each, requiring the candidates to both think and write
determine if a person matches the profile of a crime The entire allocated time is 15 minutes.
suspect.5 •Every word has a 15-second time limit within which participants
•To screen job candidates. This is sometimes used to must read, comprehend, and write a meaningful immediate
determine if people are suited to particular roles, thought that occurs to them upon first viewing the word before
especially positions that require coping with stress and moving on to the next word.
evaluating vague situations such as military leadership
•Time Limit is essential for assessing a candidate’s natural
and law enforcement positions.
response.
•Example:
In a marketing study for a family product, a researcher might •The two flashed words appear simultaneously without any
show an image of a family at a dinner table and ask the pause. By using their serial numbers, the words’ sequence must
participant to describe the story behind the scene. Their be maintained. Only after flashing the 60th word does the exam
response can reveal their views on family dynamics, come to an end.
emotional needs, or product preferences.
•For the Word Association Test (WAT) section of the SSB Interview, 1.Flexible and Adaptive:
three types of words are displayed. The open-ended nature of depth interviews enables
•Negative Words – (Cheat, Noise, Terror, Distress, Evil) researchers to adjust the flow of questions based on the
•Neutral Words – (Help, House, Proposal, Father, Mother, Child) participant's responses. If a particular topic seems interesting
•Positive Words – (Loyal, Great, Attractive, Funny, Ambitious) or important, the interviewer can explore it further, which helps
•The candidate’s mind may come up with a variety of ideas related in discovering new themes that were not anticipated before the
to each word, but he or she must write the first spontaneous research began.
response. 2.Understanding Complex Behaviors:
5. Discuss the role and relevance of depth interviews in exploratory In exploratory research, understanding the "why" behind
research. human behavior is crucial. Depth interviews help in analyzing
how individuals think, reason, and make decisions. This is
Depth interviews are a key qualitative method used in exploratory
especially useful when studying customer journeys, brand
research to gather detailed and insightful information from
perceptions, or personal experiences.
individuals. These are one-on-one, unstructured or semi-
Relevance in Exploratory Research
structured conversations that allow researchers to explore a
1.Foundation for Further Research:
participant’s thoughts, motivations, experiences, and feelings in
Exploratory research often serves as the starting point of a
depth.
larger research process. Depth interviews help generate
Role of Depth Interviews
hypotheses, identify variables, and develop ideas that can
1.Uncovering Hidden Insights:
later be tested through quantitative methods like surveys or
Depth interviews allow researchers to go beyond surface-level
experiments.
answers. Since the setting is private and conversational,
2.Effective When Little is Known:
respondents are more likely to open up about sensitive or
When a topic is new or not well understood, depth interviews
personal topics. This makes depth interviews ideal for uncovering
are extremely useful because they provide rich, detailed data.
hidden needs, attitudes, or emotional drivers that may not emerge
in group discussions or surveys.
For example, if a company is entering a new market or 4. Length: 30 Minutes to 1 Hour or More
launching an innovative product, depth interviews can provide Depth interviews usually last from 30 minutes to over an hour,
initial understanding of consumer expectations and potential depending on how much the participant has to share and how
challenges. deep the conversation goes.
3.Useful for Sensitive Topics: 5. Conducted in a Private and Comfortable Setting
In cases involving personal health, financial issues, or social The setting of the interview is carefully chosen—it could be a
stigma, respondents may not feel comfortable sharing their quiet room, a private office, or even a relaxed online space
views in a group. One-on-one interviews provide a safe where the participant feels safe.
environment where they can speak more freely and honestly.
1. Unstructured or Semi-Structured Format 6.Compare the Likert Scale and the Graphic Rating Scale.
In a depth interview, the conversation doesn’t follow a strict set 1. Likert Scale
of questions like a survey. Instead, it is either unstructured, The Likert Scale is a verbal rating scale used in surveys and
meaning completely open-ended and free-flowing, or semi- questionnaires to measure attitudes, opinions, or perceptions.
structured, meaning the interviewer has a few guiding It presents a statement and asks respondents to rate their level
questions but can adjust them based on the flow of of agreement or disagreement on a scale (typically 5 or 7
conversation. points).
2. One-on-One Interaction Example:
Depth interviews are always conducted individually—just one "I am satisfied with the product."
participant and one interviewer. There’s no group involved. •Strongly Agree
3. Open-Ended Questions •Agree
Rather than “yes” or “no” questions, depth interviews use •Neutral
open-ended questions like “Why do you feel that way?” or “Can •Disagree
you explain your experience?” •Strongly Disagree
Feature Likert Scale Graphic Rating Scale
A verbal rating scale used to measure attitudes A visual scale (usually a line or slider) where
Definition or opinions with fixed choices. respondents indicate their rating.

Series of statements followed by fixed A horizontal or vertical line where respondents

Format response options (e.g., 5 or 7 points). mark their position between two ends.

Discrete categories (e.g., Strongly Agree to Continuous response—can place a mark

Response Type Strongly Disagree). anywhere along the scale.

Ordinal – shows the order of preference but Interval – assumes equal spacing between
Measurement Level not the exact difference between options. points if numerically measured.

Requires more thought to place a precise

Ease of Use (For Respondents) Very easy to understand and respond to.
mark. Slightly more complex.
Requires conversion of marks into numbers for
Ease of Analysis (For Researchers) Simple to code and analyze.
analysis. Slightly complex.

More engaging visually, especially in digital

Visual Appeal Text-based and simple appearance. format (e.g., sliders or smiley faces).

Limited to agreement, satisfaction, or Can be used for feelings, emotions, intensity,

Flexibility frequency statements. and satisfaction with more freedom.

Surveys measuring attitudes, satisfaction, Rating pain levels, customer satisfaction, or

Examples of Use agreement (e.g., "I like this brand"). emotional reactions (e.g., UX feedback).

Quick opinion-based surveys with predefined Detailed emotional or intensity-based

Best Suited For responses. evaluations needing flexible input.
Advantages of Likert Scale: 2. Graphic Rating Scale
1.Easy to Understand and Use: The Graphic Rating Scale is a visual measurement tool
Respondents can easily choose from familiar options without much where respondents indicate their level of a feeling,
confusion. satisfaction, or opinion by placing a mark along a continuous
2.Quick to Administer: line or slider, usually between two extremes.
Surveys can be completed quickly, especially useful in large-scale Example:
research. | Very Unsatisfied ――――――――――― Very Satisfied |
3.Quantifiable Data: Advantages of Graphic Rating Scale:
Responses can be converted into numbers for easy statistical 1.Flexible and Detailed:
analysis. Allows respondents to express their opinion more precisely,
4.Standardized Format: giving richer data.
Makes comparison between different groups or over time 2.Visually Engaging:
straightforward. More attractive and interactive, especially for digital surveys
Disadvantages of Likert Scale: 3.Less Restrictive:
5.Central Tendency Bias: Unlike fixed options, respondents can indicate exact
Respondents often choose the middle option (e.g., "Neutral") to intensity of their feelings.
avoid expressing true feelings. 4.Good for Emotional or Sensitive Topics:
6.Limited Depth: Useful in UX studies, psychology, or where numeric ratings
It does not explore the reasons behind a person’s opinion—only the feel too impersonal.
direction and strength. Disadvantages of Graphic Rating Scale:
7.Misinterpretation of Scale Distance: 5.Harder to Analyze:
Assumes equal spacing between choices, which may not reflect Marks need to be converted into numerical values before
actual opinion strength. statistical analysis.
8.Cultural Differences:
Some cultures avoid extreme responses, which can affect results.
2.Subjective Marking: Step 2: Identify the Dimensions of Satisfaction
Placement of the mark may be inconsistent among different Once the objective is set, identify the key factors (dimensions)
respondents. that influence customer satisfaction. This can be done through:
3.Requires Interpretation Tools: •Literature reviews •Product Performance
Researchers must define how they’ll measure distances on the •Customer interviews •Delivery Speed
scale. •Focus group discussions •Staff Behavior
4.Less Familiar to Some Respondents: •Expert opinions •Pricing
May confuse those who aren’t used to visual scales, especially •After-Sales Support
in paper-based formats.
•Example
Step 3: Dimensions:
Generate Items (Statements or Questions)
7.Describe the process of developing a scale for measuring
Now, create statements or questions related to each satisfaction
customer satisfaction.
dimension. These items should cover all aspects of the
Creating a scale to measure customer satisfaction involves
customer's experience.
systematic steps that ensure the scale is reliable, valid, and
Example Items:
effective. This process typically includes both qualitative and
•“The product met my expectations.”
quantitative techniques to understand and quantify how
•“The staff was courteous and helpful.”
satisfied customers are with a product, service, or experience.
•“The service was delivered on time.”
Step 1: Define the Objective
The first step is to clearly define what you want to measure. Try to include both positive and negative items to avoid
Customer satisfaction can relate to various aspects such as: response bias.
•Product quality Service experience
•Value for money Timeliness
•Customer support Overall experience
Goal: Decide whether you're measuring overall satisfaction or
specific dimensions of it.
Step 5: Pretest the Scale (Pilot Testing) Step 8: Finalize and Administer the Scale
Before using the scale widely, conduct a pilot test Once tested and validated, finalize the scale and administer it
with a small group of customers to: to your target population—either online, via phone, or through
•Check clarity of items physical surveys.
•Identify confusing or biased questions Collect responses and analyze the data to gain insights into
•Measure initial reliability customer satisfaction levels and areas of improvement.
Make sure to gather feedback on how easy or hard it
was to understand and answer the questions. Define Objective
Step 6: Refine the Scale ↓
Based on the pilot test feedback, revise or remove Identify Key Dimensions
weak items, unclear questions, or redundant ↓
content. You may need to: Generate Scale Items (Statements)
•Reword confusing statements ↓
•Remove irrelevant items Choose Response Format (Likert, Graphic, etc.)
•Add missing aspects based on customer feedback ↓
This ensures the scale becomes more accurate and Pilot Test the Scale
meaningful. ↓
Step 7: Test Reliability and Validity
Revise and Refine Based on Feedback
Use statistical techniques to assess the quality of the
↓
scale:
Test Reliability and Validity
•Reliability: Check if the scale gives consistent results
↓
using Cronbach’s Alpha or Test-Retest Method.
Finalize and Distribute the Scale
•Validity: Ensure the scale measures what it claims to,
using Content Validity, Construct Validity, or
Criterion Validity.
8.Illustrate application of research in two functional Example: A company tests two different Instagram ads to see
business areas (e.g., marketing, HR). which one gets more engagement.
d. Product Development:
1. Application of Research in Marketing
Marketing research guides the development of new products or
Marketing research helps businesses understand what
improvements based on customer needs and feedback.
customers want, how to reach them, and how to improve
Example: Feedback from users reveals a flaw in a product's
products/services. It supports decision-making related to
packaging, so the company redesigns it for better usability.
branding, pricing, promotion, product development, and
2. Application of Research in Human Resources (HR)
customer engagement.
🔍 Purpose:
📌 Key Applications:
HR research supports employee-related decisions such as
a. Customer Behavior Analysis:
recruitment, training, performance, motivation, and workplace
Marketers use surveys, interviews, and focus groups to learn
satisfaction. It ensures a better working environment and
about customer preferences, buying habits, and satisfaction.
improves employee retention and productivity.
Example: A company launches a new mobile phone and
📌 Key Applications:
conducts research to find out why customers prefer a
a. Employee Satisfaction Surveys:
competitor’s brand.
b. Market Segmentation: HR uses structured questionnaires to assess employee
Research helps divide the target market into segments based on satisfaction with management, culture, and benefits.
age, gender, income, or lifestyle. Example: An IT firm conducts an annual survey to see if
Example: A skincare company uses demographic research to employees are happy with work-from-home policies.
market anti-aging products to women over 40 and acne b. Recruitment Strategy Research:
products to teenagers. Analyzing hiring trends, sourcing channels, and candidate
c. Advertising Effectiveness: feedback helps HR design better recruitment plans.
Companies measure the impact of advertising campaigns using Example: HR research shows that most qualified candidates
pre-test/post-test methods, A/B testing, or feedback surveys. apply through LinkedIn, so the company focuses more on social
media hiring.
 c. Training Needs Analysis (TNA):
functions, or phenomena systematically and accurately. It
Through observation, interviews, and performance data, HR
answers the “what,” “where,” “when,” and “how” questions but
identifies skill gaps in employees.
does not investigate “why.” This research provides a detailed
Example: Research reveals that employees lack skills in data
picture of the subject through methods like surveys, case
analytics, so HR arranges targeted training workshops.
studies, and observational studies. For example, describing
d. Retention and Turnover Research:
consumer behavior patterns or demographic characteristics.
HR studies why employees leave and what factors contribute
4.Explanatory (or Causal) Research
to job satisfaction and retention.
Explanatory research seeks to explain the causes and effects of
Example: Exit interviews and trend analysis show high
a phenomenon. It goes beyond description by investigating
turnover due to limited career growth opportunities.
relationships between variables and determining causality. This
9.Describe different types of research based on purpose and research is often hypothesis-driven and uses experiments or
methodology. longitudinal studies to test theories and understand why
Types of Research Based on Purpose something happens.
1.Exploratory Research 5.Applied Research
This type of research aims to explore a problem or topic that is Applied research is conducted to solve practical problems and
not clearly defined or understood. It is usually conducted when improve processes, products, or services. It is goal-oriented,
there is little prior knowledge available, helping to gather aiming at immediate application of findings to real-world
insights, ideas, and understand the nature of the problem. situations. For example, developing new technologies or
Exploratory research is flexible and open-ended, often involving improving healthcare methods.
qualitative methods like interviews, focus groups, or 6.Fundamental (or Basic) Research
observations. It does not provide conclusive answers but sets Fundamental research focuses on advancing theoretical
the stage for further study. knowledge without immediate practical application. It aims to
2.Descriptive Research increase understanding of fundamental principles and concepts,
Descriptive research focuses on describing characteristics, often serving as the foundation for applied research.
Types of Research Based on Methodology 4.Experimental Research
1.Qualitative Research Experimental research tests cause-and-effect relationships by
Qualitative research explores phenomena in-depth through manipulating one or more independent variables and observing
non-numerical data such as words, images, or objects. It the effect on dependent variables under controlled conditions.
focuses on understanding meanings, experiences, and It often involves random assignment and control groups to
perspectives from the viewpoint of participants. Methods minimize bias.
include interviews, focus groups, ethnography, and content 5.Non-Experimental Research
analysis. It is flexible and context-rich but typically involves Non-experimental research observes variables as they naturally
smaller sample sizes and subjective analysis. occur without manipulation. It includes correlational studies,
2.Quantitative Research case studies, and observational research, useful for
Quantitative research deals with numerical data and uses understanding relationships but not for proving causality.
statistical, mathematical, or computational techniques to 4.Applied Research
analyze results. It seeks to quantify variables, identify patterns, •Problem-solving oriented with practical applications.
and test hypotheses with larger sample sizes for generalization. •Focuses on real-world issues or improving processes/products.
Common methods include surveys with closed-ended •Often conducted in organizational or field settings.
questions, experiments, and longitudinal studies. •Results are directly used for decision-making or innovation.
3.Mixed-Methods Research •Time-sensitive and goal-driven.
Mixed-methods research combines both qualitative and 5.Fundamental (Basic) Research
quantitative approaches within a single study. It leverages the •Seeks to expand knowledge and understanding without
strengths of both to provide a more comprehensive immediate application.
understanding. For example, a researcher might conduct •Theoretical and abstract in nature.
surveys (quantitative) to identify trends and then follow up •Often conducted in academic or lab environments.
with interviews (qualitative) to explore reasons behind those •Forms the foundation for future applied research.
trends. •Focused on long-term contribution to science.
 1.Exploratory Research •Flexible design and often exploratory.
•Flexible and open-ended, allowing changes during the study. •Contextual and rich in detail.
•Conducted when the problem is not well-defined or 2.Quantitative Research
understood. •Uses numerical data and statistical analysis.
•Uses qualitative methods like interviews and observations. •Seeks to quantify variables and relationships.
•Helps generate hypotheses rather than test them. •Structured and standardized data collection methods.
•Provides initial insights and understanding, not definitive •Larger sample sizes for generalization.
answers. •Objective and replicable.
2.Descriptive Research •Uses surveys, experiments, and numerical measurements.
•Systematic and structured to provide an accurate depiction. 3.Mixed-Methods Research
•Focuses on “what,” “where,” “when,” and “how” aspects. •Combines qualitative and quantitative data collection and analysis.
•Uses surveys, case studies, and observations. •Provides comprehensive and triangulated insights.
•Does not explore causes or effects, only describes. •Addresses complex research questions.
•Data is often quantitative but can be qualitative. •Can follow sequential or concurrent design.
3.Explanatory (Causal) Research •Requires expertise in both methodologies.
•Aims to explain relationships and causes between variables. •Balances numeric data with detailed understanding.
•Hypothesis-driven and seeks to test theories. 4.Experimental Research
•Often involves experiments or longitudinal studies. •Manipulates independent variables to observe effects.
•Seeks to establish cause-and-effect. •Includes control and experimental groups.
•Uses controlled methods to reduce bias and confounding •Random assignment to reduce bias.
factors. •Seeks causality and strong internal validity.
Characteristics of Research Based on Methodology •Highly controlled environment.
1.Qualitative Research •Uses hypothesis testing.
•Data is non-numerical: words, images, or objects.
•Emphasizes depth over breadth.
5.Non-Experimental Research testing the same individuals with the same instrument at two
•No manipulation of variables; observational. different points.
•Examines relationships or patterns as they naturally occur. 1.Inter-Rater Reliability: Measures the degree to which
•Includes correlational, descriptive, and case studies. different observers or raters give consistent estimates or scores.
•Lower control over confounding variables. 2.Internal Consistency Reliability: Ensures that the items within
•Cannot prove causality but can suggest associations. a test (like survey questions) measure the same underlying
•Useful for exploratory and descriptive purposes. concept. (Cronbach's Alpha is often used here.)
10.Explain the concept of reliability and how it differs 3.Parallel Forms Reliability: Compares two versions of the same
from validity.--give answer in detail test to see if they produce similar results
Concept of Reliability Example of Reliability:
Reliability refers to the consistency or stability of a research If a thermometer consistently shows the same temperature for
instrument or measurement over time. If a method or tool the same substance in the same condition, it is considered
yields the same results under the same conditions repeatedly, reliable.
Concept of Validity
it is said to be reliable. It answers the question: “Can the Validity refers to the accuracy or truthfulness of a measurement –
results be trusted to be consistent?” in other words, whether the tool or method actually measures what
Characteristics of Reliability: it is intended to measure. It answers the question: “Does it measure
•Consistency: The results remain the same when the same
what it claims to measure?”
object or subject is measured again under similar conditions. Characteristics
•Reproducibility: When repeated by different people or at •Accuracy: The measurement truly reflects the concept it is
different times, the measurement still gives similar outcomes. supposed to measure.
•Dependability: Reliable tools provide a dependable basis for •Relevance: The questions or items are directly related to the
making conclusions. intended subject.
Types of Reliability: •Meaningfulness: The results derived from the tool are useful and
1.Test-Retest Reliability: Checks consistency over time by applicable.
Types of Validity: Aspect Reliability Validity
1.Content Validity: Ensures the measurement covers all aspects
of the concept. For example, a math test must include all
Consistency of Accuracy of what is
relevant topics from the curriculum. Meaning
results being measured
2.Construct Validity: Determines if the tool truly measures the
theoretical concept (or “construct”) it claims to measure. Truthfulness and
3.Criterion-Related Validity: Measures how well one test Repetition and
Focus relevance of
consistency
predicts outcomes based on another well-established test or measurement
criteria. This includes:
1. Predictive Validity (predicts future performance), A test can be
A test cannot be
Can exist without reliable but not
2. Concurrent Validity (compares with current valid unless it is
the other? valid (e.g.,
performance). also reliable
consistently wrong)
Example of Validity:
If a weighing machine measures your weight correctly A bathroom scale The scale actually
according to your actual weight, it is valid. If it shows more or Example shows 60kg every shows your correct
less than your true weight, it's not valid – even if it's consistent time (reliable) weight (valid)
every time. Necessary for
Requires reliability
Relation validity, but not
Conclusion: as a foundation
sufficient
While reliability ensures that results are repeatable and
consistent, validity ensures that the results are accurate and
meaningful. In high-quality research, both are essential — a tool
must measure consistently (reliable) and measure the correct
thing (valid) to be considered effective.
 11.Illustrate the four levels of measurement with appropriate determine how much higher or lower. For example, consider a
real-world examples. give answer in detail customer satisfaction survey where responses are recorded as
1. Nominal Level of Measurement “Very Unsatisfied,” “Unsatisfied,” “Neutral,” “Satisfied,” and
The nominal level is the simplest and most basic form of “Very Satisfied.” These categories have a clear order from low to
measurement. It involves categorizing data into distinct high satisfaction, but the gap between “Neutral” and “Satisfied”
groups that do not have any order or ranking. These may not be the same as the gap between “Satisfied” and “Very
categories are used only to name or label different items or Satisfied.” Likewise, class ranks (1st place, 2nd place, 3rd place)
characteristics, and the values cannot be compared in terms also represent ordinal data because the positions are ranked
of magnitude. Since nominal data are purely qualitative, we but don’t reveal how close the scores were. Ordinal data is
can only count how many observations fall into each useful for expressing preferences or opinions, but it cannot
category, but we cannot perform any mathematical support complex mathematical operations like averaging.
operations on them. For example, consider the classification 3. Interval Level of Measurement
of people based on their blood type — A, B, AB, or O. Each The interval level of measurement includes all the features of
label represents a different group, but one type is not ordinal data but goes further by having equal and measurable
“greater” or “lesser” than another. Similarly, gender (male, intervals between values. This means we can not only rank the
female, other) or nationality (Indian, Japanese, Canadian) are data, but we can also measure the exact differences between
nominal categories. The key point is that nominal data only them. However, interval data does not have a true zero point,
identifies and classifies without any quantitative meaning or which means ratios cannot be calculated meaningfully. A good
order. example is temperature measured in Celsius or Fahrenheit. The
2. Ordinal Level of Measurement difference between 20°C and 30°C is the same as the difference
The ordinal level of measurement adds a layer of complexity between 30°C and 40°C — a 10-degree interval. But saying that
by introducing a meaningful order or ranking among the 40°C is “twice as hot” as 20°C would be incorrect because 0°C
categories. However, the differences between these ranks does not represent a complete absence of temperature.
are not measurable or uniform. In other words, we can say Another example is IQ scores or dates on a calendar
that one value is higher or lower than another, but we cannot
Although these scales allow for arithmetic operations like Concept of Control and Treatment Groups
addition and subtraction, multiplication and division are not In research, especially in experimental studies, the concepts of
valid because there is no absolute zero. control group and treatment group are used to determine the
4. Ratio Level of Measurement effectiveness of a variable or intervention. The treatment
The ratio level is the highest and most informative level of group (also known as the experimental group) is the group that
measurement. It possesses all the characteristics of interval receives the intervention, treatment, or change introduced by
data — such as ordering and equal intervals — but it also the researcher. On the other hand, the control group does not
includes a true, absolute zero point. This allows for all types of receive the treatment; it remains under normal or standard
mathematical operations, including addition, subtraction, conditions. The key purpose of having a control group is to
multiplication, and division. A true zero means the complete provide a baseline for comparison, which helps researchers
absence of the measured variable. For example, weight is a isolate the actual effect of the treatment by comparing
ratio variable — 0 kilograms means no weight at all, and 10 outcomes between the two groups.
kilograms is exactly twice as heavy as 5 kilograms. Similarly, Both groups are ideally randomly assigned to ensure fairness
height, age, income, and distance are ratio-level measurements and minimize bias. By comparing the results between the
because they can be compared meaningfully in terms of ratios treatment and control groups, researchers can determine
(e.g., someone earning ₹40,000 earns twice as much as whether the changes observed are truly caused by the
someone earning ₹20,000). Because of the presence of an treatment or by some other external factors.
absolute zero, ratio data is the most robust and flexible for Real-World Research Scenario: Testing a New Educational App
statistical analysis. Let’s say a team of researchers wants to study whether using a
12. Apply the concept of control and treatment groups in a new mobile learning app improves students' math
real-world research scenario performance in high school.
Step 1: Forming Groups
They take a sample of 200 students from the same grade and
divide them randomly into two equal groups:
 •Treatment Group (100 students): These students use the new selecting an appropriate sampling frame is crucial. The
educational app for math practice every day for 3 months. sampling frame is the actual list or source from which the
•Control Group (100 students): These students continue with sample of respondents is drawn. If it is not well-defined, the
traditional classroom learning and use regular textbooks entire research could be flawed or biased. Below are the
without the app. practical steps to determine an appropriate sampling frame in
Step 2: Observation and Data Collection this context, explained in detail:
At the end of 3 months, both groups take the same 1. Define the Target Population Clearly
standardized math test. The researchers then compare the The first and most important step is to clearly define who your
average scores between the treatment and control groups. study is about. In the case of customer satisfaction in retail, the
Step 3: Analyzing Results target population could be "customers who have made a
If the treatment group (who used the app) scores significantly purchase from the retail store within the past three months."
higher than the control group, the researchers may conclude The definition must be specific and measurable, including
that the app had a positive impact on learning. However, if relevant details like:
there is no significant difference, it might mean that the app •Age group (if needed), Location (such as a specific city or
had little or no effect. region),Purchase history or frequency,
Why It Matters •Type of retail store (grocery, clothing, electronics, etc.).
This method helps ensure that any difference in performance is This ensures that the sampling frame includes only relevant
likely due to the app itself and not other factors like individual individuals whose feedback will be meaningful to your research
intelligence, teacher quality, or prior knowledge — because 2. Identify Available Sources of Customer Information
both groups were treated equally, except for the intervention. Once the target population is defined, the next step is to identify
where you can find a list of potential respondents. In a retail
13 -Explain the practical steps to determine an appropriate
setting, possible sources for creating a sampling frame may
sampling frame in a research study on customer satisfaction in
include:
retail.
•Customer databases from the store's loyalty or membership
To conduct a research study on customer satisfaction in retail,
programs,Email subscriber lists,Billing and transaction records,
 3. Ensure the Sampling Frame is Representative
•Stratified sampling: customers are divided into sub-groups
The sampling frame must include a diverse and balanced set of
customers who reflect the actual characteristics of your target (e.g., age, region, shopping frequency), and samples are taken
population. For instance, if your customer base includes all age from each.
•Systematic sampling: select every 10th or 20th customer from
groups and income levels, then your sampling frame should not
only include customers who use your app (who might be the list.
•Cluster sampling: use specific branches or store locations as
younger or more tech-savvy), as that would cause sampling
bias. Try to include online and offline buyers, regular and clusters.
occasional shoppers, and different demographic groups. Your sampling technique should match your research goals and
4. Remove Duplicates and Ineligible Entries the structure of your sampling frame.
Before using the sampling frame, clean the data to remove any 6. Test and Validate the Sampling Frame
duplicates, irrelevant entries, or incomplete records. For Before launching the full survey, test the frame with a pilot
example, remove: survey to see if the respondents represent the wider population
•Entries without contact information, accurately. Check whether the responses are diverse, balanced,
•People who haven’t shopped in years (if they're no longer and useful. If not, you may need to revise the sampling frame by
relevant), including more data sources or adjusting your selection method.
•Internal staff or suppliers accidentally included in the database.
This step ensures your sample is accurate, clean, and ready for Conclusion
sampling. In summary, creating an appropriate sampling frame for a retail
5. Determine the Sampling Technique customer satisfaction study involves clearly defining the
After finalizing the sampling frame, decide how you will select population, using reliable sources, ensuring representativeness,
respondents from it. This could be: cleaning the data, choosing the right sampling technique, and
•Simple random sampling: every customer has an equal validating your frame. These steps help ensure the study results
chance. are accurate, unbiased, and actionable for decision-making in
retail business strategy.
 14. Compare close-ended and open-ended questions in researcher is exploring new ideas, gaining detailed feedback, or
questionnaire design. understanding the underlying reasons behind certain behaviors
Close-Ended Questions or attitudes. For instance, a question like “What do you think we
Close-ended questions are those that provide respondents with can do to improve your shopping experience?” invites
a limited set of predefined options to choose from. These respondents to share unique and insightful feedback that might
could be simple “Yes” or “No” responses, multiple-choice not be captured through fixed options. While open-ended
options, rating scales (like 1 to 5), or checkboxes. One of the questions provide richer and more in-depth data, they are
main advantages of close-ended questions is that they are easy often time-consuming to answer and analyze, as the responses
to analyze quantitatively, since the responses can be easily need to be reviewed, categorized, and interpreted manually or
categorized, counted, and compared using statistical tools. They through qualitative analysis methods. Additionally, some
are particularly useful when the researcher wants to measure respondents may skip these questions if they feel they are too
specific attributes or attitudes and maintain consistency in long or require more effort.
responses. For example, asking “How satisfied are you with our
service?” followed by options like “Very Satisfied, Satisfied,
Neutral, Dissatisfied, Very Dissatisfied” allows for quick and
uniform responses. However, the major limitation of close-
ended questions is that they may restrict the depth and
richness of feedback, as respondents are confined to the
choices provided, which might not reflect their true opinion.
Open-Ended Questions
Open-ended questions, on the other hand, do not limit the
respondent’s answers. They allow individuals to express their
thoughts, feelings, and opinions freely in their own words.
These types of questions are particularly valuable when a
Aspect Close-Ended Questions Open-Ended Questions
Questions with predefined answer Questions that allow free-form,
Definition
options. descriptive answers.
Fixed options (e.g., Yes/No, multiple No fixed options; respondents write their
Response Format
choice, scales). own answers.

Type of Data Collected Quantitative (measurable, countable). Qualitative (descriptive, subjective).

Difficult and time-consuming; requires

Ease of Analysis Easy to analyze using statistical tools.
coding or thematic analysis.

Depth of Information Limited depth; surface-level insights. Rich, detailed insights and opinions.

Requires more effort and thought; may

Respondent Effort Requires less effort; quicker to complete.
lead to skipped responses.
Ideal for structured surveys with large Ideal for exploring ideas, opinions, or
Usefulness in Surveys
samples. unknown factors.
"Are you satisfied with our service?" "What do you think about our customer
Examples
(Yes/No) service?"
High consistency; easier to compare Low consistency; answers vary widely in
Consistency of Responses
across respondents. length and detail.

Flexibility of Answers Restricted to the given options. Allows full freedom to express thoughts.
15.Discuss the elements that make a research problem well- time, budget, access to data, and research skills. A well-defined
defined. problem should take into account the limitations and
1. Clarity and Specificity constraints of the researcher. For instance, attempting to study
A well-defined research problem must be clear and specific. global consumer behavior with limited funds and no
This means the problem should not be vague, general, or broad. international data access would not be feasible. Instead,
Instead, it should be narrowed down to a particular issue or narrowing it down to a specific city or region makes it more
gap that the research intends to address. Clarity allows both the manageable.
researcher and the audience to fully understand what is being 4. Relevance and Significance
studied. For example, instead of stating “Customer A good research problem must be important and relevant to a
dissatisfaction in retail,” a more specific problem would be specific field of study or real-world issue. It should address a
“Investigating the impact of long checkout times on customer gap in knowledge, solve a practical problem, or contribute to
dissatisfaction in urban retail stores.” This ensures the research theory-building. The problem should matter to researchers,
remains focused and purposeful. practitioners, or decision-makers. If a problem is too trivial or
2. Researchability
has already been extensively studied without any need for
The problem should be researchable, meaning it must be
further exploration, it may not be worth researching. A relevant
possible to investigate it through empirical methods—like
research problem helps justify why the study is needed.
surveys, experiments, observations, or data analysis. Abstract or 5. Objectivity and Neutrality
philosophical questions may be interesting, but they may not be The problem must be framed in an objective and unbiased
suitable for practical research unless they can be translated into manner. It should not lead to a predetermined conclusion or
measurable variables. A researchable problem allows the reflect the researcher’s personal opinions. For example, instead
researcher to collect data, analyze it, and draw meaningful of asking “Why are employees unhappy with bad
conclusions. management?” a more neutral version would be “What are the
3. Feasibility factors affecting employee satisfaction in the workplace?”
Feasibility refers to whether the research problem can be Objectivity ensures that the research is fair and based on
realistically studied within the available resources—such as evidence rather than assumptions.
 6. Relationship Between Variables (If Applicable) 1. Identifying the Research Problem
In quantitative research, a well-defined problem often The very first step in the research process is to identify and define a
includes the relationship between variables. For example, clear research problem or question. This involves recognizing an
“What is the effect of social media advertising on consumer issue or gap in knowledge that needs to be addressed. A well-
buying behavior?” clearly identifies an independent defined problem guides the entire study and helps focus the
variable (social media advertising) and a dependent research efforts. At this stage, the researcher should ensure that the
variable (buying behavior). This element helps in problem is specific, researchable, and relevant.
developing hypotheses and research questions later in the 2. Reviewing the Literature
process. Once the problem is identified, the next step is to conduct a
7. Alignment with Research Objectives
thorough review of existing literature related to the topic. This
Lastly, a well-defined problem should align with the
involves gathering and analyzing previous studies, theories, and
research objectives and questions. It acts as the foundation
findings to understand what is already known and where gaps
for the entire study. If the problem is poorly defined, the
exist. Literature review helps the researcher build a theoretical
rest of the research process—literature review,
foundation, avoid duplication, and refine the research problem
methodology, data analysis—can become disjointed. A well-
or hypothesis.
framed problem provides direction and structure to the
study, guiding every subsequent step in a logical and 3. Formulating Hypothesis or Research Questions
cohesive way. Based on the literature review and problem definition, the
Conclusion researcher develops hypotheses or research questions. A
In summary, for a research problem to be well-defined, it must hypothesis is a tentative statement predicting a relationship
be clear, specific, researchable, feasible, relevant, objective, between variables, while research questions seek to explore or
and in many cases, show a relationship between variables. explain aspects of the problem. This step sets the direction for
These elements ensure the research has purpose, clarity, and the study by providing clear goals for data collection and
structure, leading to credible and useful results. analysis.
16. Analyze the steps involved in the research process.
 4. Designing the Research This step involves explaining what the results mean, discussing
In this step, the researcher decides on the research design and implications, and identifying limitations. The final findings are
methodology. This includes selecting whether the study will be then compiled into a research report or paper that
qualitative, quantitative, or mixed-methods, and choosing communicates the study’s outcomes clearly to the intended
appropriate data collection methods (surveys, interviews, audience.
experiments, etc.). The researcher also determines the 8. Drawing Conclusions and Making Recommendations
sampling strategy, tools, and procedures to ensure that the The last step is to draw conclusions based on the research
data collected will be valid and reliable. findings and offer recommendations for practice, policy, or
5. Collecting Data further research. This ensures that the research has practical
After the design is finalized, the researcher proceeds to collect value and contributes to the body of knowledge. Researchers
data according to the chosen methods. This step involves often suggest how future studies can build on their work or
administering surveys, conducting interviews, performing address any remaining questions.
experiments, or gathering secondary data. Proper data
collection is critical as it directly affects the accuracy and 17. Compare exploratory and descriptive research
credibility of the research findings. designs with examples.
6. Analyzing Data Exploratory Research Design
Once data is collected, the next step is to analyze it using Exploratory research is conducted when the researcher has a
appropriate statistical or qualitative techniques. Data analysis limited understanding of the problem and seeks to gain insights
involves organizing, summarizing, and interpreting the data to and familiarity with the topic. This type of research is often
test hypotheses or answer research questions. For quantitative unstructured and flexible, aiming to explore new ideas, discover
data, this might include statistical tests, while qualitative data patterns, or clarify concepts without focusing on definitive
analysis might involve coding and thematic analysis. answers. It helps in formulating hypotheses and designing more
7. Interpreting and Reporting Results precise studies later on. Exploratory Research Design
Following analysis, the researcher interprets the findings in Exploratory research is conducted when the researcher has a
the context of the research problem and existing literature. limited understanding of the problem and seeks to
Feature Exploratory Research Descriptive Research
The main purpose is to investigate an unclear or poorly The primary aim is to describe the existing
Purpose understood problem. It helps researchers gain a deeper characteristics or behavior of a group or situation in
understanding and formulate hypotheses. a clear, organized, and quantifiable manner.

It follows an unstructured or semi-structured format where the It is highly structured and systematic, often involving
Structure process is flexible and open-ended to adapt as insights emerge. well-planned steps and tools to gather specific
information about the subject being studied.

Usually conducted in the initial stages of research when the Conducted after enough groundwork has been
Research Stage problem is not well defined or when no clear direction is known. done, often following exploratory research, to gather
data that supports conclusions and decision-making.

Involves a qualitative approach using open-ended questions and Uses a quantitative approach, though sometimes
Approach flexible techniques to understand deeper meanings and ideas. qualitative methods are also used. It focuses more on
measuring and analyzing specific variables.

Data is collected using formal methods like

Data is gathered using informal or non-standardized methods like structured surveys, standardized questionnaires, and
Data Collection personal interviews, observations, focus groups, and content statistical analysis techniques to ensure precision and
analysis. accuracy.

Uses closed-ended or multiple-choice questions, like

Nature of Questions Uses open-ended questions like "Why do users behave this way?" "How often do you use this product?" or "What is
or "What problems are women facing with this product?" your age group?"

Less flexible, as it follows a predetermined plan and

Flexibility Highly flexible—researchers can change the direction as new focuses on consistency in data collection across
insights are discovered. participants.
gain insights and familiarity with the topic. This type of 1. Ensures Accuracy and Reliability of Results
research is often unstructured and flexible, aiming to A good research design acts like a blueprint for the entire study.
explore new ideas, discover patterns, or clarify concepts It outlines how data will be collected, analyzed, and interpreted.
without focusing on definitive answers. It helps in When the design is well-structured, it minimizes errors, biases,
formulating hypotheses and designing more precise studies and inconsistencies, which directly improves the accuracy
later on. (closeness to the true value) and reliability (consistency of
Example results) of the findings. For instance, using random sampling
Suppose a tech company wants to launch a wearable device and standardized tools helps produce more dependable and
for women's safety but doesn’t know what features female valid data.
users need most. They might conduct exploratory research 2. Controls for Bias and Confounding Variables
by interviewing a small group of women, studying social In any research, biases and confounding factors (variables that
trends, and analyzing crime statistics to gather insights. influence both the dependent and independent variables) can
Descriptive Research Design distort the results. A good research design includes strategies
Descriptive research is conducted to describe like control groups, randomization, or matching techniques to
characteristics, behaviors, or functions of a group or control these external influences. This ensures the relationship
situation. It is more structured and is used when the being studied is valid and not manipulated by hidden variables,
researcher already has some understanding of the topic. strengthening internal validity.
Example 3. Helps Establish Cause-and-Effect Relationships
A retail company wants to know what percentage of its One of the key goals of certain research studies, especially
customers are aged between 20 and 30 and how often experimental ones, is to establish causal relationships. A strong
they shop online. It would use a structured questionnaire design includes appropriate techniques such as pre-tests, post-
and analyze the data using descriptive statistics. tests, and control groups. These elements support causal
18.Explain the importance of a good research design in inference by proving that the independent variable truly caused
ensuring research validity. changes in the dependent variable, rather than it being a
coincidence or due to another factor.
4. Improves Generalizability (External Validity) 7. Supports Logical Flow and Consistency
External validity is about how well the findings apply to the real From problem identification to data interpretation, a good
world or other populations. A well-designed research study research design promotes a logical and consistent flow. Every
ensures that the sample represents the target population step connects with the next, maintaining clarity and coherence.
properly, and the setting of the study is realistic. This makes the When the research process is well-aligned, the results are more
findings more generalizable to a larger group, not just the likely to be valid because they reflect a systematic investigation
participants involved in the study. rather than a haphazard process.
5. Enhances Ethical Standards and Clarity Long Answers Question
Ethical issues can impact the validity of research if participants 1.Draft a sample research proposal on “The Impact of Social
are misled, harmed, or data is manipulated. A good design Media on Consumer Buying Behavior”.
includes clear ethical guidelines, informed consent processes, 1. Introduction
and honest reporting methods, which help maintain both the In the digital age, social media platforms such as Instagram,
integrity and credibility of the research. When the study is Facebook, YouTube, and TikTok have transformed the way
ethical and transparent, the data becomes more trustworthy consumers interact with brands and make purchasing decisions.
and valid. Social media is not only a communication tool but also a
6. Provides Direction and Saves Time powerful marketing channel that influences consumer behavior
A well-structured research design helps researchers stay through advertisements, influencer endorsements, peer
focused and avoid unnecessary data collection or confusion. It reviews, and user-generated content. This research aims to
clearly defines the problem, objectives, tools, timeline, and explore how social media platforms impact consumer buying
procedures in advance. This saves time and resources while behavior, particularly in terms of trust, perception, and
also ensuring the research remains methodologically sound, purchasing decisions.
which indirectly supports validity by reducing distractions or
missteps.
2. Statement of the Problem 4.Is there a correlation between time spent on social media and the
Traditional marketing methods are rapidly being replaced frequency of purchases?
or supplemented by digital strategies, especially those 5. Hypothesis H₀ (Null Hypothesis): Social media does not significantly
involving social media. However, the exact extent to influence consumer buying behavior.
which social media affects consumer behavior—both H₁ (Alternative Hypothesis): Social media significantly influences
positively and negatively—is not fully understood. This consumer buying behavior.
research seeks to fill that gap by analyzing the 6. Scope of the Study This research will focus on consumers aged 18–
relationship between social media engagement and 35 who actively use social media platforms in urban areas. It will
consumer buying decisions. particularly explore purchasing behavior in the fashion, beauty, and
3. Objectives of the Study electronics sectors, as these are most commonly promoted on social
•To examine the influence of social media marketing on media.
consumer purchase intentions. 7. Research Methodology
•To analyze the role of influencers and peer reviews on a. Research Design Descriptive and exploratory research design will be
purchasing decisions. used to understand patterns and relationships.
•To identify which social media platforms have the b. Data Collection Method
strongest impact on buying behavior. •Primary Data: Online questionnaires and interviews with 100
•To assess consumer trust in social media advertisements respondents.
and promotions. •Secondary Data: Previous research papers, marketing reports, and
4. Research Questions online articles.
1.How does social media influence consumer awareness c. Sampling Method
and interest in products? Convenience sampling will be used to collect data from active social
2.What role do social media influencers play in shaping media users in metropolitan cities.
consumer preferences? d. Data Analysis Tools
3.Which types of content (videos, stories, reviews, etc.) Statistical tools such as SPSS or Excel will be used to analyze data using
are most effective in driving purchases? frequency tables, charts, and regression analysis.
8. Significance of the Study
This research will be helpful for marketers, brand strategists, 10 .What is meant by non-response in sampling? Why is it a
and companies to understand consumer behavior trends and concern?(very short answer)
optimize their social media marketing strategies. It also Non-response in sampling refers to a situation where some
benefits consumers by making them more aware of how their individuals selected for a sample do not provide the required
purchasing choices may be influenced by digital platforms. data. In other words, they fail to respond to a survey,
9. Limitations of the Study questionnaire, interview, or any other method of data
•The study is limited to a small sample size due to time and collection. This can occur for various reasons — people may be
resource constraints. unwilling, unavailable, or unable to participate in the study.
•Responses may be biased based on individual perceptions or Why it is a concern--
internet literacy. Non-response is a concern because it can lead to biased results
•Only certain product categories and demographics are if the people who do not respond are different from those who
considered. do. This affects the accuracy and representativeness of the
10. Tentative Chapter Plan data, making it less reliable. It also reduces sample size,
1.Introduction increases error margins, and may require complex adjustments,
2.Review of Literature which can make the research less valid and more costly.
3.Research Methodology
4.Data Analysis and Interpretation
5.Findings, Suggestions, and Conclusion
11. Conclusion
As the digital space continues to evolve, it is essential to
understand the role that social media plays in influencing
consumers. This research will contribute to the growing field
of digital consumer behavior and offer actionable insights for
both marketers and consumers.