MCA-249
Research Methodology
How research is actually done — defining a problem and a hypothesis, collecting and measuring data, sampling and analysis, then writing it up in LaTeX.
- Semester
- Semester 3
- Credits
- 3
- Scheme
- 3 lectures a week
- Contact hours
- 44 across four units
- Category
- Open Elective - II
What the paper is
Research Methodology is the paper that prepares the dissertation. It is taught from Kothari and it moves in the order a project does: define the problem, form a hypothesis, design the study, collect the data, sample it, analyse it, and write it up.
The measurement material in Unit II is the part most often underestimated. Validity and reliability, and the four levels of measurement — nominal, ordinal, interval, ratio — determine which analysis is legitimate later, and getting them wrong invalidates everything downstream.
Unit IV is unusually practical for a methodology paper: technical writing in LaTeX and citation management in Zotero or Mendeley. Both are tools you will use for the dissertation in the fourth semester, and both are faster to learn now than under deadline.
What to concentrate on
- Be able to write a null and an alternative hypothesis for a given research question, and to state the Type I and Type II errors in that context. It is the most commonly asked short question.
- Know the probability sampling methods — simple random, systematic, stratified, multi-stage — with when each is appropriate. Comparisons with non-random sampling are the standard long answer.
- For Unit III, the chi-square test of association, computed on a small contingency table, is the reliable numerical question, and it overlaps with Statistics and Data Analytics.
Syllabus, unit by unit
Summarised from the approved scheme. Hours are the contact hours the scheme allots, which is a fair guide to where the marks sit.
Unit I · Fundamentals of research and hypothesis
12 hours- Meaning, objectives and significance of research; types of research; research methods versus methodology
- The research process and the criteria of good research; defining the research problem and techniques for doing so
- Research design: meaning, need, features of a good design, different designs, basic principles of experimental design
- Ethics in research; formulating a research title and a criteria-based proposal
- Problem identification and formulation, research and investigation questions, measurement issues
- Questionnaire design and the features of a good questionnaire
- Hypothesis: qualities of a good hypothesis, null and alternative hypotheses, the logic and importance of testing
Unit II · Data collection and measurement
10 hours- Methods of primary and secondary data collection
- Metrics: throughput, latency, overhead, reliability, precision, recall, running time, accuracy, discomfort
- Measurement: what is measured, measurement scales, problems of validity and reliability
- Levels of measurement: nominal, ordinal, interval and ratio
Unit III · Sampling and data analysis
12 hours- Statistical population, sample, sampling frame, sampling error, sample size, non-response
- Characteristics of a good sample
- Probability sampling: simple random, systematic, stratified random and multi-stage sampling
- Determining sample size and practical considerations
- Data preparation and univariate analysis: frequency tables, bar charts, pie charts, percentages
- Bivariate analysis: cross tabulations and the chi-square test, including testing a hypothesis of association
Unit IV · Technical writing and citation management
10 hours- The significance of report writing; structure and components of a report
- Types of report: research papers, theses, project reports
- Introduction to technical writing with LaTeX
- Citation management with Zotero or Mendeley: fundamentals of citations, citation styles, managing citations and bibliographies
How it is examined
- Question 1 is compulsory, covers the whole syllabus, and is made of objective or short-answer questions. It carries 12 marks.
- The rest of the paper is four units matching the four above. Each unit sets two questions and you attempt one, so there are four more answers at 12 marks each.
- Examiners are asked to map every question to a course outcome using Bloom's taxonomy, which is why questions are phrased as “apply”, “analyse” or “evaluate” rather than only “explain”.
The pass mark is 40 out of 100 in every paper.
Learning objectives
- Fundamentals of experiment design and statistics
- Reading and analysing research papers
- Data processing
- Paper writing and citation management
- Oral presentations
Assumed beforehand
- Basic statistics
- Basic applied mathematics
Books it is taught from
- TB1C. R. Kothari, “Research Methodology: Methods & Techniques”, New Age International, 4th edition, 2019
- TB2Leslie Lamport, “LaTeX: A Document Preparation System”, Pearson Education, 2nd edition, 2006
- TB3Deepak Chawla and Neena Sondhi, “Research Methodology: Concepts and Cases”, Vikas Publications, 2nd edition, 2016
Notes for MCA-249
Lecture notes, question papers and assignments filed against MCA-249 are in the library. Everything there has been checked by a moderator before it appears, and an account is free — new ones are approved by hand, which is what keeps the shelf clean.