| Lecture No. |
Description |
Lecture By |
| Lecture 1 |
Introduction to Business Research |
Lecture by Dr. Sandeep Kumar, Lecture by B, Lecture by C, Lecture by D |
| Lecture 2 |
Type of Research |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 3 |
Process of Research |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 4 |
Formulation of the Research Problem |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 5 |
Concept of Hypothesis, Development of the Research Hypotheses |
Lecture by Dr.Sandeep Kumar, Lecture by Dr.Sandeep Kumar, Lecture by C, Lecture by D |
| Lecture 6 |
Types of Hypotheses |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 7 |
Research Design-Definition, Functions |
Lecture by Dr. Sandeep Kumar, Lecture by B, Lecture by C, Lecture by D |
| Lecture 8 |
Types of Research Design-Exploratory, Descriptive & experimental |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 9 |
Experimental Research Design – Pre-experimental, Quasi-experimental |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 10 |
Experimental Research Design-True experimental, Statistical application of various Research Designs |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 11 |
Validity of research instruments-face & content |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 12 |
Construct Validity; Readability of Research Instruments |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 13 |
Internal Consistency Procedures |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 14 |
Methods of Data collection-Primary & Secondary Sources |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 15 |
Concept of Attitude |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 16 |
Attitude Scales Likert, Thurstone |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 17 |
Guttman Scales |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 18 |
Concept of Questionnaire |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 19 |
Types of Questionnaire |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 20 |
Questionnaire Designing |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 21 |
Concept of Sampling |
Lecture by Dr. Sandeep Kumar, Lecture by B, Lecture by C, Lecture by D |
| Lecture 22 |
Concept of Sampling Design |
Lecture by Dr.Sandeep Kumar, Lecture by B, Lecture by C, Lecture by D |
| Lecture 23 |
Types of Sampling Design-Probability, Non-probability |
Lecture by Dr.Sandeep Kumar, Lecture by Dr.Sandeep Kumar, Lecture by C, Lecture by D |
| Lecture 24 |
Various Probability Sampling Design |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 25 |
Various Non-Probability Sampling Design |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 26 |
Mixed Sampling Designs |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 27 |
Sampling Frame |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 28 |
Sample Size Determination |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 29 |
Data Processing |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 30 |
Data Editing, Coding |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 31 |
Use of Tabulation in Data Processing |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 32 |
Data analysis-Univariate, bivariate |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 33 |
Multivariate Data Analysis |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 34 |
Hypothesis Testing-Concept |
Lecture by Dr.Sandeep Kumar, Lecture by B, Lecture by C, Lecture by D |
| Lecture 35 |
Types of Error |
Lecture by Dr.Sandeep Kumar, Lecture by B, Lecture by C, Lecture by D |
| Lecture 36 |
Steps in hypothesis testing |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 37 |
Parametric Tests |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 38 |
Non-Parametric Tests |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 39 |
Anova |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 40 |
Correlation Analysis, Regression Analysis |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 41 |
Chi-Square Test |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 42 |
Non-Parametric Tests for Normality |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 43 |
Runs Test |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 44 |
Advanced Data Analysis Techniques-Basic Concepts of Factor Analysis |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 45 |
Discriminate Analysis. Conjoint Analysis |
Lecture by A, Lecture by B, Lecture by C, Lecture by D |
| Lecture 46 |
Research Proposal |
Lecture by Dr.Sandeep Kumar, Lecture by Dr.Sandeep Kumar, Lecture by C, Lecture by D |