Learning outcome (at course level) |
Learning and teaching strategies |
Assessment Strategies |
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On completion of this course, the students will be able to:
CO49: Be able to distinguish between a population and a sample CO50: Know how to conduct a statistical test of a hypothesis. CO51: Be able to evaluate the criteria that can be used to select an appropriate statistical test to answer a research question or hypothesis. CO52: To select an appropriate statistical test to answer a research question or hypothesis. CO53: Be able to distinguish between the writing structure used for a quantitative study and one used for a qualitative study. CO54: Create and apply the Knowledge of new applications and the recent trends in the subject. |
Approach in teaching: Interactive Lectures, Discussion, Tutorials, assignments.
Learning activities for the students: Self-learning assignments, Effective questions, Giving tasks |
Class test, Semester end examinations, Quiz, Solving problems in tutorials, Assignments, Individual projects |
• Concept of Permutation and Combinations
• Probability: Basic Concepts, Importance of Concept of Probability, Theorem of Probability (Additional Theorem and Multiplication Theorem), Conditional Probability, Bayes’ Theorem, Mathematical Expectation
• Probability Distribution: Binomial, Poisson’s and Normal.
• Sampling: Meaning of census and sample. Characteristics of a good sample, Need for sample, Types of samples based on Probability and Non-Probability sampling. Probability Sampling- Idea of Simple Random Sampling, Stratified and Cluster sampling Non- Probability Sampling- Purposive and Quota sampling.
• Sampling Distribution and Standard Error: Element of Testing a Statistical Hypothesis- Formulation of the problem, Types of Errors. Level of Significance
• Unit III: 20 Hrs
• Analysis of Parametric Test: Test of Significance for Large and Small samples.
• Analysis of Variance: Application of F-test. One-way and Two-way classification.
• Analysis of Non -parametric Tests :
• Chi-square Test: Chi-square test for population variance. Chi-Square Test (goodness of fit, independence of attributes using 2x2 and rxc contingency tables).
• sign test, Wilcoxon signed rank test, Friedman test, Kruskal-Wallis test, Mann-Whitney test
• Analysis of Non -parametric Tests :
• Chi-square Test: Chi-square test for population variance. Chi-Square Test (goodness of fit, independence of attributes using 2x2 and rxc contingency tables).
• sign test, Wilcoxon signed rank test, Friedman test, Kruskal-Wallis test, Mann-Whitney test
•Research Report Writing: Types and layouts of research reports, Steps in report writing, Essentials of a good report, Presentation, Footnote- Endnote, Bibliography, References
• Simpson and Kafka: Basic Statistics, Oxford and IBH Publishers.
• Badarkar, P.L. and Wilkinson T.S. (2000), Methodology and Techniques of Social Research, Himalaya Publishing House, Mumbai
• Business Statistics-Gupta, Goyal, Jain, Biyani, Gupta ( Ajmera Book Company)
• Kothari, C.R.( Second Edition), Research Methodology- Methods and Techniques, Wishwa Publication, New Delhi.
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