Research Methodology CR Kothari — Past Paper OmpathStudy

Research Methodology — Reference and Study Guide This source is a 418-page reference textbook, not a question paper. Its numbered examples and exercises must not be treated as a question count. The guide below follows the complete 15-chapter structure and directs study of the attached source pages. 1. Research methodology: an introduction Meaning, objectives, motivations, types and approaches to research; scientific method; the research process; criteria for good research. 2. Defining the research problem Selecting, narrowing and clearly stating a research problem and the steps used to make it operational. 3. Research design Purpose and features of good designs, major design types, experimental principles and development of a research plan. 4. Sampling design Census versus sample surveys, sampling steps, selection criteria, probability and complex random-sampling designs. 5. Measurement and scaling Measurement scales, error, reliability and validity, development of measurement tools and scale-construction techniques. 6. Methods of data collection Observation, interviews, questionnaires, schedules, secondary sources, case studies and choosing an appropriate collection method. 7. Processing and analysis of data Editing and coding data; descriptive statistics; measures of central tendency, dispersion, skewness and relationships; regression and correlation. 8. Sampling fundamentals Sampling distributions, central limit theorem, standard error, estimation and determination of sample size. 9. Parametric hypothesis testing Hypotheses, errors, significance, power, test procedures and tests involving means, proportions, variances and correlations. 10. Chi-square testing Variance comparison, non-parametric applications, assumptions, calculation steps, corrections and cautions. 11. Analysis of variance and covariance One-way and two-way ANOVA, Latin-square designs, ANOCOVA, analysis tables and assumptions. 12. Non-parametric testing Distribution-free tests, their selection, application and relationship to rank-based measures. 13. Multivariate analysis Classification and application of multivariate techniques, factor analysis, rotation, R/Q analysis and path analysis. 14. Interpretation and report writing Interpreting findings, report structure, writing process, presentation, mechanics and precautions. 15. The computer in research Computer-system concepts, binary representation, applications and the role of computing in research workflows. Recommended study sequence Define the problem → choose a research design → select a sample → develop valid measurement tools → collect and process data → choose appropriate statistical tests → interpret results → write and present the report. Statistical workflow reminder Identify the variable type and study design first. Then check assumptions, select the test, state hypotheses, choose the significance level, calculate or obtain the test statistic and p-value, interpret the result in context, and report uncertainty and limitations.