Introduction to Research Methodology, Objectives, Types of Research and the Research Process

1. CONTENTS:
• R E S E A R C H - M E A N I N G
• O B J E C T I V E S O F R E S E A R C H
• T Y P E S O F R E S E A R C H
• R E S E A R C H A P P R O A C H E S
• I M P O R T A N C E O F R E S E A R C H
• R E S E A R C H P R O C E S S
• C R I T E R I A F O R A G O O D R E S E A R C H
• P R O B L E M S E N C O U N T E R E D B Y R E S E A R C H E R S I N I N D I A
UNIT 1- Notes by Ms. Anubala. S, Asst. Professor, Shri Krishnaswamy College
for Women

2. What is Research?
Defining Research
 Common Parlance: A search for knowledge.
 Scientific & Systematic: A search for pertinent information on a specific topic.
 Art of Scientific Investigation: A careful inquiry, especially for new facts.
 "Systematized effort to gain new knowledge." (Redman & Mory)
 Movement from Known to Unknown: A voyage of discovery driven by
inquisitiveness.
According to Clifford Woody: Research is defined as “ a process that Defines and
redefines problems, formulates hypotheses, collects and evaluates data, makes
deductions, reaches conclusions, and tests them.”

3. Objectives of Research
 To discover answers to questions using scientific procedures.
 To uncover hidden or undiscovered truths.
Broad Groupings of Research Objectives:
 Exploratory or Formulative Research:
 To gain familiarity with a phenomenon.
 To achieve new insights into a topic.
 Descriptive Research:
 To accurately portray the characteristics of an individual, situation, or group.
 Diagnostic Research:
 To determine the frequency of something's occurrence.
 To determine its association with something else.
 Hypothesis-Testing Research:
 To test a hypothesis about a causal relationship between variables.

4. • D E S C R I P T I V E V S . A N A L Y T I C A L R E S E A R C H
• A P P L I E D V S . F U N D A M E N T A L R E S E A R C H
• Q U A N T I T A T I V E V S . Q U A L I T A T I V E R E S E A R C H
• C O N C E P T U A L V S . E M P I R I C A L R E S E A R C H
BASIC TYPES OF RESEARCH

5. Descriptive vs. Analytical Research
Descriptive Research:
• Surveys and fact-finding inquiries.
• Describes the "state of affairs" as it exists.
• Often termed "Ex post facto research" in social science/business.
• Researcher has no control over variables; reports what happened/is happening.
• Examples: Frequency of shopping, consumer preferences.
• Methods: Survey methods (comparative, correlational).
Analytical Research:
• Uses existing facts/information.
• Analyzes material to make a critical evaluation.

6. Applied vs. Fundamental Research
Applied (Action) Research:
• Aims to solve an immediate problem (society, industry, business).
• Examples: Identifying market trends, marketing research, evaluation research.
• Goal: Discover a solution for a pressing practical problem.
Fundamental (Basic or Pure) Research: Concerned with generalizations
and theory formulation.
• "Gathering knowledge for knowledge’s sake."
• Examples: Research on natural phenomena, pure mathematics, human behavior for
generalizations.
• Goal: Add to the existing organized body of scientific knowledge.

7. Quantitative vs. Qualitative Research
Quantitative Research:
• Based on measurement of quantity or amount.
• Applicable to phenomena expressed in numerical terms.
Qualitative Research:
• Concerned with qualitative phenomena (quality or kind).
• Aims to discover underlying motives and desires (e.g., Motivation Research).
• Techniques: In-depth interviews, word/sentence/story completion tests, projective
techniques.
• Examples: Attitude or opinion research.
• Crucial in behavioral sciences to understand human behavior motives.

8. Conceptual vs. Empirical Research
Conceptual Research:
• Related to abstract ideas or theories.
• Used by philosophers/thinkers to develop or reinterpret concepts.
Empirical Research (Experimental):
• Relies on experience or observation alone (data-based).
• Conclusions are verifiable by observation or experiment.
• Involves firsthand data collection from the source.
• Researcher formulates a working hypothesis and actively manipulates variables to
prove/disprove it.
• Strongest support for a hypothesis comes from empirical evidence.

9. Some Other Types of Research
Based on Time:
 One-time Research: Confined to a single time-period.
 Longitudinal Research: Carried on over several time-periods.
Based on Environment:
 Field-setting Research: Conducted in natural environments.
 Laboratory Research: Conducted in controlled laboratory settings.
 Simulation Research: Uses models or simulations.
Clinical or Diagnostic Research:
 Follows case-study methods or in-depth approaches.
 Aims to reach basic causal relations, often with small samples and deep probing.

10. Some Other Types of Research
Exploratory vs. Formalized Research:
 Exploratory: Develops hypotheses (not tests them).
 Formalized: Substantial structure with specific hypotheses to be tested.
Historical Research:
 Utilizes historical sources (documents, remains) to study past events/ideas.
Conclusion-oriented vs. Decision-oriented Research:
 Conclusion-oriented: Researcher has freedom to pick problem, redesign,
conceptualize.
 Decision-oriented: Driven by the need of a decision-maker (e.g., Operations
Research).

11. Research Approaches: Quantitative vs. Qualitative
1. Quantitative Approach
 Focus: Generating data in quantitative (numerical) form for rigorous analysis.
 Sub-classifications:
 Inferential Approach:
 Experimental Approach:
 Simulation Approach:
2. Qualitative Approach
 Focus: Subjective assessment of attitudes, opinions, and behavior.
 Nature: Relies on researcher's insights and impressions.
 Output: Non-quantitative results or data not subjected to rigorous quantitative analysis.
 Techniques: Focus group interviews, projective techniques, depth interviews.

12. Significance of Research
1. Economic Policy & Governance (e.g., assessing needs,
revenue forecasting)
2. Business & Industry (eg., Operations research for cost
minimization/profit maximization)
3. Social Sciences (eg., Explores social relationships and addresses
societal problems)

13. Significance of Research
4. Career Advancement: For students pursuing higher
degrees (Master's, Ph.D.).
5.Livelihood: For professionals in research methodology.
6. New Ideas & Insights: For philosophers and thinkers.
7. Creative Development: For literary individuals.
8. Theoretical Generalizations: For analysts and
intellectuals.

14. • A sc i e n t i fi c ap pr o ac h t o s o l v i n g a r e s e a r c h pr o b l e m .
• Fo c u s e s o n ho w r e se ar c h i s do n e s y st e m a t i c a l l y an d l o g i c a l l y .
W HY W A S T HE S T U D Y U N D E R T A K E N ?
HO W W A S T HE R E S E A R C H P R OB L E M D E F I N E D ?
W HA T M E T H OD S W E R E U S E D A N D W HY ?
Understanding Research Methodology

15. Research Process

17. • F i r st a n d m o st c r i t i c a l st e p i n s c i e n t i fi c i n q u i r y .
• T w o t y pe s:
• State of nature problems
• Relationship between variables
S t e p s:
• U n d e r st an d t h e p r o b l e m t h o r o u g h l y .
• R e ph r a se i n t o c l e ar , an a l y t i c al t e r ms .
• E v a l u a t e fe a s i b i l i t y b e fo r e fi n a l i z i n g .
Step 1: Formulating the Research Problem

18.  W r i t e a b r i e f s u m m a r y o f t h e r e s e a r c h p r o b l e m .
E x p l o r e :
• A b s t r a c t i n g & i n d e x i n g j o u r n a l s
• B i b l i o g r a p h i e s ( p u b l i s h e d o r u n p u b l i s h e d )
• A c a d e m i c j o u r n a l s & c o n f e r e n c e p r o c e e d i n g s
• G o v e r n m e n t r e p o r t s , b o o k s , a n d o t h e r s c h o l a r l y s o u r c e s
R e s o u r c e f u l H u b s :
• U n i v e r s i t y L i b r a r i e s
• D i g i t a l R e p o s i t o r i e s & D a t a b a s e s
• P r e v i o u s S t u d i e s O n S i m i l a r T o p i c s
Step 2: Extensive Literature Survey

19. 🧪 Step 3: Development of Working Hypotheses
✅ Definition
• A tentative assumption made to test logical or empirical consequences.
• Acts as the focal point of research.
Purpose & Significance
• Delimits the scope of the research.
• Guides thinking and keeps the study focused.
• Determines data requirements and analysis methods.
How to Develop Hypotheses
📘 Discuss with colleagues & experts.
️
🗂️Examine existing data and records.
📚 Review similar or past studies.
🧭 Conduct exploratory field interviews.

20. 🧭 Step 4: Preparing the Research Design
What Is a Research Design?
• A conceptual framework for conducting research.
• Ensures efficient data collection with minimal effort, time, and cost.
Purpose-Driven Design Categories
• Exploration – flexible, broad scope
• Description – emphasizes accuracy and objectivity
• Diagnosis – identifies causes or conditions
• Experimentation – tests relationships with rigor

21. 🧭 Step 4: Preparing the Research Design
Types of Research Designs
Non-experimental
Experimental
Informal: e.g., before-and-after (with/without control)
Formal: randomized, block, Latin square, factorial designs
Key Considerations
📋 Means of gathering information
👥 Skill and availability of research team
🧠 Logical organization of methodology
⏳ Time constraints
💰 Budget and funding resources

22. Step 5: Understanding Sample Design
What Is a Sample?
• A sample is a subset selected from a population or universe.
• A census covers the entire population but is often impractical due to cost,
time, or bias risks.
What Is Sample Design?
• A predetermined plan for selecting a sample from the population.
• Aims for efficiency, cost-effectiveness, and minimal bias.
Types of Samples
• Probability Samples: Known chance of selection.
• Non-Probability Samples: No known probability of selection.

23. Step 5: Understanding Sample Design
Sampling Type Description
Deliberate (Purposive)
Based on researcher’s judgment for
representativeness. Ideal for qualitative research.
Convenience
Selects accessible units (e.g. people at a petrol
station). Risk of bias if population varies.
Judgmental
Uses expert judgment to identify key
representatives.
Quota
Interviewers fill a set number (quota) from different
subgroups—structured but not random.
Non-Probability Sampling Methods

24. Step 5: Understanding Sample Design
Sampling Type Description
Simple Random
Equal chance for every unit; e.g., lottery draw,
or random number tables.
Systematic
Choose every nth unit from a list. Adds
randomness at start.
Stratified
Divide population into homogeneous
subgroups (strata), sample each using random
methods.
Probability Sampling Methods

25. Step 5: Understanding Sample Design
Sampling Type Description
Cluster Sampling
Select entire groups (clusters), not individual
units. Useful for efficiency in field work.
Area Sampling
Divide a large geographic area into smaller
zones; randomly choose zones.
Multi-stage
Sampling
Sample in stages—e.g., States Districts Cities
→ →
Households.
→
Sequential Sampling
Sample size is not fixed; evolves as data is
analyzed. Used in quality control.
Probability Sampling Methods

26. Step 6: Collecting the Data – Approaches & Methods
Why Collect Data?
• Existing data often prove inadequate for real-world problems.
• Appropriate data collection improves accuracy, relevance, and research validity.
Primary Data Collection
• Experiment: Quantitative measurements to test hypotheses.
• Survey Methods:
 Observation: Investigator notes real-time behavior without interaction.
 Personal Interviews: Structured Q&A with respondents.
 Telephone Interviews: Fast and useful for industrial or time-sensitive research.
 Mail Questionnaires: Widely used; requires thoughtful design and pilot testing.
 Schedules: Trained enumerators collect responses through face-to-face interactions.

27. Step 6: Collecting the Data – Approaches & Methods
Choosing the Right Method
Factors to Consider
• Nature and objective of the investigation
• Financial resources available
• Time constraints
• Required degree of accuracy
• Researcher’s skills and experience

28. Step 7: Execution of the Project
Importance of Execution
• Ensures accurate, adequate, and dependable data.
• Must follow a systematic and timely approach.
Data Collection Methods
• Structured Questionnaires: Machine-processable with coded
responses.
• Interviews: Requires trained interviewers and clear manuals.
Quality & Supervision
• Field checks ensure sincerity and efficiency.
• Survey should be under statistical control to maintain accuracy.
Handling Non-response
• Identify non-respondents and sample them.
• Use expert intervention to maximize responses.

29. Step 8 : Analysis of Data
Steps in Data Analysis
• Classification & Coding: Convert raw data into symbolic,
countable categories.
• Editing & Tabulation: Clean data and organize into tables.
• Use of Technology
Computers assist in processing large datasets quickly and
efficiently.
• Drawing Inferences
Compute percentages, coefficients, etc., using statistical formulas.
Test hypotheses using significance tests:
Example: Difference in means between wage samples.
Example: Analysis of Variance (ANOVA) for crop yields.
• Final Goal
Derive meaningful insights with valid and reliable conclusions.

30. Step 9: Hypothesis Testing
• Conducted after data analysis to evaluate formulated hypotheses
• Key question: Do the facts support the hypothesis?
• Common statistical tests:
Chi-square test
t-test
F-test
• Outcomes: Hypothesis is accepted or rejected
• No hypothesis? Use data-based generalisations as future hypotheses
Step 10: Generalizations & Interpretation
• Repeatedly supported hypotheses can lead to theories
• Core aim of research: derive general principles
• No initial hypothesis? Findings may be explained via
interpretation
• Interpretation may lead to new research questions

31. Step 11: Preparation of the Report or Thesis
• Preliminary Pages: Title, date, acknowledgements, foreword,
table of contents, list of tables/charts
• Main Text:
• Introduction: Objectives, methodology, scope, limitations
• Summary of Findings: Non-technical, concise
recommendations
• Main Report: Logically sequenced sections
• Conclusion: Clear restatement of research results
• End Matter: Appendices, bibliography, index
Writing Style & Presentation
• Simple, objective language — avoid vague terms
• Use charts/illustrations only for clarity
• Mention confidence limits and research constraints

32. Problems Faced by Researchers in India
 Lack of Training: Insufficient knowledge of research
methodology; need for intensive short-term courses
 Weak Industry-Academia Link: Poor liaison with
businesses/government limits access to real-world data
 Data Confidentiality Concerns: Reluctance of firms to share
data due to fears of misuse
 Duplication of Effort: Overlapping studies due to lack of research
registries and topic tracking
 No Code of Conduct: Inter-departmental rivalries and absence of
ethical guidelines hinder collaboration

33. Problems Faced by Researchers in India
 Limited Secretarial Support: Delays due to inadequate
administrative and computing help
 Inefficient Libraries: Time lost finding sources instead of
analyzing content
 Delayed Access to Govt. Publications: Especially problematic
in non-metro libraries
 Inconsistent Published Data: Agencies vary in coverage;
hampers reliability
 Conceptual & Collection Issues: Challenges in defining
problems and gathering quality data