Research Methodology — Study Notes for PhD Entrance Exam

UNIT 1: Research and Types of Research

1.1 Meaning of Research

In everyday usage, research simply means a search for knowledge. More precisely, it is a scientific and systematic search for pertinent information on a specific topic — an art of scientific investigation. Research can be thought of as a movement from the known to the unknown: a voyage of discovery driven by human inquisitiveness, which is often called the “mother of all knowledge.”

Notable definitions of research:

• The Advanced Learner’s Dictionary of Current English describes it broadly as a careful, in-depth inquiry aimed at uncovering new facts within a field of knowledge.
• Redman and Mory describe it as a systematized effort directed at gaining new knowledge.
• D. Slesinger and M. Stephenson (in the Encyclopaedia of Social Sciences) frame it as the manipulation of concepts, things, or symbols in order to generalize, extend, correct, or verify knowledge — knowledge that can support either theory-building or the practice of an art.
• Clifford Woody describes research as a process of defining and redefining a problem, formulating hypotheses or possible solutions, collecting and organizing data, drawing deductions, and finally testing whether the conclusions support the original hypothesis.

Synthesis: Research is, at its core, an original contribution to the existing stock of knowledge — a pursuit of truth carried out through study, observation, comparison, and experiment. It is the objective, systematic search for a solution to a problem, as well as the systematic effort behind generalization and theory formulation. Formally, the term covers the full sequence: stating the problem → formulating a hypothesis → collecting data/facts → analyzing the facts → reaching conclusions (either a solution to the problem or a broader theoretical generalization).

Key characteristics of research:

• Systematic and controlled
• Empirical (based on observable evidence)
• Objective and logical
• Replicable and verifiable
• Aims at generalization or theory-building

1.2 Objectives of Research

The purpose of research is to discover answers to questions through the application of scientific procedures — its central aim being to uncover truths that have not yet been discovered. While every research study has its own specific purpose, research objectives generally fall into four broad groupings:

1. Exploratory (Formulative) research – to gain familiarity with a phenomenon or achieve new insights into it.
2. Descriptive research – to accurately portray the characteristics of a particular individual, situation, or group.
3. Diagnostic research – to determine the frequency with which something occurs, or the extent to which it is associated with something else.
4. Hypothesis-testing research – to test a hypothesized causal relationship between variables.

Broadly, research also serves to:

• Discover new facts / verify old facts
• Analyze events/processes to establish cause-effect relationships
• Develop new tools, concepts, or theories
• Find solutions to practical/scientific problems
• Contribute to the existing knowledge base

1.3 Motivation in Research

What drives people to undertake research? The possible motives include one or more of the following:

1. Desire to obtain a research degree and its associated benefits
2. Desire to face the challenge of solving unsolved problems — i.e., concern over practical problems that initiates research
3. Desire to experience the intellectual joy of doing creative work
4. Desire to be of service to society
5. Desire to gain respectability

This is not an exhaustive list. Additional factors can also motivate — or at times compel — people to undertake research, including:

• Directives from government or employer bodies
• Employment conditions requiring research output
• Curiosity about new things
• Desire to understand causal relationships
• Broader social thinking and awakening
• Requirements of the job (contract research, consultancy)

MCQ

Objective Type MCQ on Meaning of Research- Objectives of Research- Motivation in Research

1.4 Significance of Research

“All progress is born of inquiry. Doubt is often better than overconfidence, for it leads to inquiry, and inquiry leads to invention” — this famous line from Hudson Maxim captures the essence of why research matters. Greater amounts of research make progress possible; research also inculcates scientific and inductive thinking, promoting logical habits of thought and organization.

Significance in government and economic policy:

• Research underlies nearly all government policy — for example, budgets rest partly on an analysis of people’s needs/desires weighed against available revenue.
• It helps devise and compare alternative policies and examine their likely consequences; while decision-making itself isn’t research, research substantially facilitates it.
• It supports resource-allocation decisions across areas like agriculture, industry, labor, trade, distribution, and defense.
• It underpins the collection of economic/social statistics that reveal what is happening in the economy and what is changing — a task requiring dedicated research staff/technicians in most governments.
• In this context, research operates in three phases: (i) investigating economic structure through continual fact-compilation, (ii) diagnosing current events and the forces behind them, and (iii) prognosis — predicting future developments.

Significance in business and industry:

• Operations research applies mathematical, logical, and analytical techniques to solve business problems of cost minimization, profit maximization, or general optimization.
• Market research investigates the structure and development of a market to shape efficient purchasing, production, and sales policies.
• Motivational research examines why people behave as they do, focusing on the motivations underlying consumer/market behavior.
• Together, these forms of research support demand forecasting, supply/capacity planning, sales estimation, business budgeting, and investment/production planning — replacing intuitive decisions with more logical, scientific ones.

Significance for social scientists:

• Research helps study social relationships and seek answers to social problems, offering both intellectual satisfaction (knowledge for its own sake) and practical utility (knowledge that helps improve how things are done).
• Social science research carries a double responsibility: developing principles that explain and predict human interactions, while also providing practical guidance for solving immediate problems in human relations.

Significance from different vantage points:

• For postgraduate/doctoral students, research can be a path to career advancement.
• For research professionals, it can be a source of livelihood.
• For philosophers and thinkers, it is an outlet for new ideas and insights.
• For writers, it fuels the development of new styles and creative work.
• For analysts and intellectuals, it generates new theoretical generalizations.

In short, research is a fountain of knowledge for its own sake and a key source of guidance for solving business, governmental, and social problems — a form of formal training that helps one better understand new developments within one’s field.

1.5 Research Methods vs Research Methodology

Aspect	Research Methods	Research Methodology
Meaning	Techniques/tools used to conduct research (e.g., data collection, statistical tools)	The science/philosophy of studying how research is done systematically
Scope	Narrower — concerned with the “how” of specific tasks	Broader — includes methods plus the logic behind choosing them
Focus	Execution of the study	Design, rationale, and validity of the research process
Includes	Techniques for collecting data, sampling methods, statistical techniques	Study design, assumptions, criteria used to evaluate methods, and their applicability

In short: Methods = the tools; Methodology = the study of which tools to use, why, and how, in a given context.

1.6 Types of Research

(a) Descriptive vs. Analytical

Descriptive research covers surveys and fact-finding enquiries of various kinds, with its main purpose being to describe the state of affairs as it currently exists. In social science and business research, this is often referred to as ex post facto research, since the defining feature is that the researcher has no control over the variables and can only report what has happened or is happening — for example, measuring shopping frequency or people’s preferences. Ex post facto studies also extend to attempts at identifying causes even where the variables cannot be controlled. Methods commonly used include surveys of all kinds, along with comparative and correlational methods.

Analytical research, by contrast, uses facts or information that already exist, analyzing this material to arrive at a critical evaluation.

(b) Applied vs. Fundamental (Basic)

Applied (action) research aims at finding a solution for an immediate problem facing a society or a business/industrial organization. Examples include research into social, economic, or political trends affecting an institution, copy research (testing whether communications are read/understood), marketing research, and evaluation research. Its central aim is to solve a specific, pressing practical problem.

Fundamental (basic/pure) research is concerned mainly with generalizations and theory formulation — “gathering knowledge for knowledge’s sake.” Examples include research into natural phenomena, pure mathematics, or human behavior aimed at broad generalizations rather than solving a specific problem. Basic research is directed toward building information with a wide base of applications, adding to the organized body of scientific knowledge.

(c) Quantitative vs. Qualitative

Quantitative research is based on measuring quantity or amount, and applies to phenomena expressible in numerical terms.

Qualitative research concerns phenomena relating to quality or kind — for example, investigating why people think or behave in certain ways falls under Motivation Research, a key type of qualitative research that seeks to uncover underlying motives and desires, typically through in-depth interviews, word-association tests, sentence-completion tests, story-completion tests, and other projective techniques. Attitude/opinion research — studying how people feel or think about a subject or institution — is also qualitative. It is especially significant in behavioral sciences for uncovering the motives behind human behavior, though applying it well is relatively difficult and often benefits from guidance by experimental psychologists.

(d) Conceptual vs. Empirical

Conceptual research relates to abstract ideas or theory, typically used by philosophers/thinkers to develop new concepts or reinterpret existing ones.

Empirical research relies on experience or observation, often without heavy regard for pre-existing system/theory. It is data-based, producing conclusions verifiable through observation or experiment — essentially an experimental type of research. The researcher must first frame a working hypothesis, then gather enough facts/data to prove or disprove it, setting up an experimental design that manipulates the persons or materials involved to generate the desired information. This type of research is marked by the experimenter’s control over the variables and deliberate manipulation of one variable to study its effect. It is the appropriate choice when proof is sought that certain variables affect others in a specific way, and is considered the strongest form of support for a hypothesis.

(e) Some Other Types of Research

All other types of research are essentially variations of the above, distinguished by purpose, time span, environment, or similar factors:

• By time: One-time research (confined to a single time period) vs. Longitudinal research (carried out across several time periods).
• By environment: Field-setting research, Laboratory research, or Simulation research.
• Clinical/diagnostic research: Uses case-study methods or in-depth approaches to trace basic causal relationships, typically going deep into causes using small samples and intensive data-gathering techniques.
• Exploratory vs. Formalized research: Exploratory research aims to develop hypotheses rather than test them, while formalized research has substantial structure with specific hypotheses to be tested.
• Historical research: Uses historical sources (documents, remains, etc.) to study past events, ideas, or the philosophy of persons/groups from an earlier era.
• Conclusion-oriented vs. Decision-oriented research: In conclusion-oriented research, the researcher is free to choose the problem, redesign the enquiry as it proceeds, and conceptualize as they wish. Decision-oriented research, by contrast, serves the needs of a decision-maker, and the researcher is not free to pursue their own inclinations. Operations research is a classic example of decision-oriented research, being a scientific method for providing executive departments with a quantitative basis for decisions on operations under their control.

MCQ

Objective Type MCQ on Types of research – Descriptive vs. Analytical, Applied vs. Fundamental, Quantitative vs. Qualitative, Conceptual vs. Empirical.

1.6.1 Research Approaches

The various types of research discussed above ultimately rest on two basic approaches: the quantitative approach and the qualitative approach.

Quantitative approach — involves generating data in numerical form, suitable for rigorous, formal quantitative analysis. It is further sub-classified into:

• Inferential approach: Builds a database from which the characteristics or relationships of a population can be inferred. This typically takes the form of survey research, where a sample is studied (questioned/observed) and its characteristics are then inferred to hold for the wider population.
• Experimental approach: Marked by much greater control over the research environment; certain variables are deliberately manipulated to observe their effect on other variables.
• Simulation approach: Involves constructing an artificial environment in which relevant information/data can be generated, allowing observation of a system’s (or sub-system’s) dynamic behavior under controlled conditions. In business and social science contexts, simulation refers to running a numerical model representing the structure of a dynamic process — given initial conditions, parameters, and exogenous variables, the simulation traces the process’s behavior over time. This approach is also useful for building models to understand future conditions.

Qualitative approach — concerned with the subjective assessment of attitudes, opinions, and behavior. Here, research outcomes depend heavily on the researcher’s own insights and impressions, and results are generated in non-quantitative form or in a form not subjected to rigorous quantitative analysis. Common techniques include focus group interviews, projective techniques, and depth interviews.

MCQ

Objective Type Question MCQ on RESEARCH APPROACHES, SIGNIFICANCE OF RESEARCH

Research Process

The research process consists of a series of closely related, often overlapping, steps:

1. Formulating the research problem – identifying and defining the problem clearly.
2. Extensive literature review – surveying existing knowledge.
3. Developing hypotheses – formulating tentative propositions.
4. Preparing the research design – deciding on the blueprint (exploratory, descriptive, experimental).
5. Determining sample design – deciding sampling technique and sample size.
6. Collecting data – through observation, interviews, questionnaires, experiments.
7. Execution of the project – actual fieldwork/data gathering under supervision.
8. Analysis of data – applying statistical/qualitative techniques.
9. Hypothesis testing – accepting or rejecting hypotheses based on analysis.
10. Generalizations and interpretation – drawing broader inferences.
11. Preparation of the report/thesis – writing up findings in a structured format.

(Note: This is a logical sequence, not strictly linear — steps often overlap and involve backtracking.)

1.7 Criteria of Good Research

A good research study should satisfy the following criteria:

1. Purpose clearly defined – objectives stated in common, unambiguous terms.
2. Research process detailed – procedures described in sufficient detail for replication.
3. Research design well planned – yields results as objective as possible.
4. High ethical standards applied – honesty and transparency maintained.
5. Limitations frankly revealed – researcher reports flaws/limitations honestly.
6. Adequate analysis for decision-making – sufficient data analysis to reveal significance.
7. Findings presented unambiguously – conclusions justified by data and methods used.
8. Conclusions confined to justified data – researcher doesn’t overgeneralize.
9. Greater confidence in research – if researcher is experienced, has good reputation, and follows ethical norms

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UNIT 2: Research Formulation — Defining and Formulating the Research Problem

2.1 Selecting the Problem

Guidelines for selecting a research problem:

• Avoid overdone/oversaturated topics unless a new approach is possible
• Avoid controversial topics for beginners unless well-suited
• Too narrow or too vague problems should be avoided
• The subject should be familiar and feasible in terms of time, cost, and resources
• Importance/urgency, suitability of the researcher, availability of data, and cost involved should guide selection

2.2 Necessity of Defining the Problem

A clearly defined problem is the foundation of good research:

• Provides direction to the research and prevents wastage of resources
• Helps determine the data to be collected and the techniques to be used
• Guards against faulty conclusions
• Enables the researcher to plan the study logically
• “A problem clearly stated is a problem half-solved” — a poorly defined problem leads to confusion at every subsequent stage.

Steps in defining a research problem:

1. Statement of the problem in general terms
2. Understanding the nature of the problem
3. Surveying available literature
4. Developing ideas through discussion (with colleagues/experts)
5. Rephrasing the problem into a working/operational form

2.3 Importance of Literature Review in Defining a Problem

A literature review helps the researcher:

• Understand what has already been done, avoiding duplication
• Identify gaps, contradictions, or unresolved issues in current knowledge
• Refine and sharpen the research problem/objectives
• Identify appropriate theoretical frameworks and methodologies used by others
• Understand terminology, variables, and measurement tools used in the field
• Build a strong rationale/justification for the proposed study

2.4 Literature Review — Sources

Primary sources: Original, firsthand accounts of research —

• Original research articles/papers published in journals
• Theses and dissertations
• Conference proceedings
• Patents
• Technical/research reports
• Raw data, lab notebooks, letters, original documents

Secondary sources: Interpretations/summaries of primary sources —

• Textbooks
• Reviews – critical summaries/evaluations of research on a topic published in review journals
• Treatises – comprehensive, systematic written accounts of a subject
• Monographs – detailed, scholarly studies focused on a single specialized topic
• Encyclopedias, handbooks
• Newspaper/magazine articles

Patents: A significant but often underused source, particularly in technical/scientific research, revealing:

• State-of-the-art technology
• Novel methods/processes/products not yet published elsewhere
• Prior art for assessing novelty of a proposed innovation

Web as a source: Search engines, digital libraries (e.g., Google Scholar, IEEE Xplore, ScienceDirect, PubMed), institutional repositories, preprint servers (e.g., arXiv), and government/organizational databases.

Searching the web effectively:

• Use specific keywords and Boolean operators (AND, OR, NOT)
• Use quotation marks for exact phrases
• Use advanced search filters (date range, publication type, subject)
• Use citation databases (Scopus, Web of Science) to trace citation trails
• Evaluate source credibility (peer-reviewed vs. non-peer-reviewed; authority of publisher)

2.5 Critical Literature Review

A critical review goes beyond summarizing — it involves:

• Comparing and contrasting different studies’ methodologies and findings
• Evaluating the strengths, weaknesses, and limitations of existing studies
• Identifying inconsistencies, contradictions, or unanswered questions
• Synthesizing findings across multiple sources into a coherent narrative
• Situating the proposed research within the existing body of knowledge

2.6 Identifying Gap Areas from Literature Review

Gaps commonly identified include:

• Knowledge gaps – areas not yet studied
• Methodological gaps – limitations in methods used by prior studies
• Contradictory findings – conflicting results needing resolution
• Population/context gaps – studies not covering certain populations, geographies, or time periods
• Practical/application gaps – theoretical work not yet tested in practice

Identifying these gaps provides the justification and novelty for the proposed research.

2.7 Development of Working Hypothesis

A working hypothesis is a tentative, testable assumption/proposition formulated to guide the research and provide a focal point for investigation.

Sources for formulating hypotheses:

• Discussions with colleagues and experts
• Examination of available literature/data
• Analogy (similar problems solved elsewhere)
• Personal experience and observation
• Exploratory/pilot studies

Characteristics of a good hypothesis:

• Clear, precise, and testable
• Stated in simple, understandable terms
• Consistent with known facts
• Limited in scope (specific, not too general)
• Capable of being tested within a reasonable time frame

UNIT 3: Data Collection and Analysis

3.1 Execution of the Research

Execution refers to the actual implementation of the research design in the field:

• Setting up the necessary organizational/administrative arrangements
• Ensuring the research proceeds strictly on schedule
• Maintaining periodic checks to ensure data quality and honesty in data collection
• Handling non-response and unforeseen field problems

3.2 Observation and Collection of Data

Data can be primary (collected firsthand) or secondary (already collected by someone else).

3.3 Methods of Data Collection

(a) Observation method – systematic viewing/recording of behavior/events as they occur (structured or unstructured; participant or non-participant).

(b) Interview method – direct verbal interaction (structured, unstructured, or focused/depth interviews).

(c) Questionnaire method – set of written questions sent/administered to respondents.

(d) Schedule method – similar to a questionnaire, but filled by the enumerator/investigator on behalf of the respondent.

(e) Other methods: Case study method, projective techniques, warranty cards, panels, focus group discussions, and secondary data sources (published reports, government publications, prior research).

3.4 Modeling and Mathematical Models for Research

Modeling involves creating a simplified representation of a real system/phenomenon to study its behavior.

Types of models used in research:

• Descriptive models – describe relationships/structures
• Predictive models – forecast future outcomes (e.g., regression models)
• Normative/optimization models – prescribe the best course of action (e.g., linear programming)
• Simulation models – replicate system behavior over time (e.g., Monte Carlo simulation)
• Mathematical/statistical models – expressed through equations (e.g., regression equations, differential equations, probability models, queuing models, Markov models)

Models help researchers simplify complexity, test hypotheses computationally, and predict outcomes under varying conditions before/without real-world experimentation.

3.5 Sampling Methods

Since studying an entire population is often impractical, researchers select a sample.

Probability sampling (random selection, every unit has known chance of selection):

• Simple random sampling
• Systematic sampling
• Stratified sampling
• Cluster sampling
• Multi-stage sampling

Non-probability sampling (selection not based on randomization):

• Convenience sampling
• Judgmental/purposive sampling
• Quota sampling
• Snowball sampling

Key considerations: sample size determination, sampling error, representativeness of the sample.

3.6 Data Processing and Analysis Strategies

Data processing steps:

1. Editing – checking data for completeness, consistency, accuracy
2. Coding – assigning numerical/symbolic values to responses for analysis
3. Classification – arranging data into groups/classes based on common characteristics
4. Tabulation – summarizing data in table form

Analysis strategies:

• Descriptive analysis – measures of central tendency (mean, median, mode), dispersion (range, variance, standard deviation), and distribution shape (skewness, kurtosis)
• Inferential/correlational analysis – correlation, regression, analysis of variance (ANOVA)
• Multivariate analysis – factor analysis, cluster analysis, discriminant analysis, multiple regression
• Qualitative analysis – thematic analysis, content analysis, coding of narrative/textual data

3.7 Data Analysis with Statistical Packages

Common statistical software used:

• SPSS (Statistical Package for the Social Sciences)
• R (open-source statistical computing)
• Python (with libraries such as pandas, NumPy, SciPy, statsmodels)
• MS Excel (basic statistical functions, data analysis toolpak)
• MATLAB, STATA, Minitab (specialized statistical/engineering computation)

These tools help perform:

• Descriptive statistics
• Hypothesis tests (t-test, chi-square, ANOVA)
• Regression and correlation analysis
• Visualization (histograms, scatter plots, box plots)

3.8 Hypothesis Testing

Hypothesis testing is a statistical procedure to decide whether to accept or reject a null hypothesis (H₀) in favor of an alternative hypothesis (H₁).

Steps in hypothesis testing:

1. State the null and alternative hypotheses
2. Select the appropriate test statistic (z-test, t-test, chi-square, F-test, etc.)
3. Set the level of significance (α, commonly 0.05 or 0.01)
4. Determine the critical region/critical value
5. Compute the test statistic from sample data
6. Compare and decide: accept or reject H₀
7. Interpret the result in context

Errors in hypothesis testing:

• Type I error – rejecting a true null hypothesis (false positive)
• Type II error – accepting a false null hypothesis (false negative)

3.9 Generalization and Interpretation

• Generalization: Extending conclusions drawn from a sample to the wider population, provided the sample is representative and the study design is valid.
• Interpretation: Explaining the meaning and implications of the findings — linking results back to the research objectives/hypotheses, situating them within existing theory/literature, and discussing practical or theoretical significance.

Good interpretation also involves:

• Acknowledging limitations and possible alternative explanations
• Avoiding over-generalization beyond the scope of the data
• Suggesting areas for further research
• Preparing the final report/thesis with clear conclusions and recommendations

Quick Revision Summary

Topic	Key Idea
Research	Systematic investigation to discover/verify knowledge
Methods vs Methodology	Tools vs. the science of choosing/justifying tools
Research types	Descriptive/Analytical, Applied/Fundamental, Quantitative/Qualitative, Conceptual/Empirical
Research process	Problem → Literature → Hypothesis → Design → Sampling → Data collection → Analysis → Testing → Interpretation → Report
Good research	Objective, well-planned, ethical, transparent about limitations
Problem formulation	Clear definition + literature review + gap identification + hypothesis
Literature sources	Primary (journals, theses, patents) vs. Secondary (reviews, treatises, monographs, textbooks)
Data collection	Observation, interview, questionnaire, schedule, case study
Sampling	Probability (random, stratified, cluster) vs. Non-probability (convenience, purposive, quota, snowball)
Analysis	Descriptive stats, inferential tests, multivariate methods, software (SPSS/R/Python)
Hypothesis testing	State H₀/H₁ → choose test → set α → compute statistic → decide → interpret

Study Notes Video

MCQ

MCQ on Meaning of Research- Objectives of Research- Motivation in Research

MCQ on Types of research – Descriptive vs. Analytical, Applied vs. Fundamental, Quantitative vs. Qualitative, Conceptual vs. Empirical.

MCQ on RESEARCH APPROACHES, SIGNIFICANCE OF RESEARCH