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Practical
This paper is designed so that the student get familiar with statistical software for solving the statistical problems based on descriptive statistics and bivariate data.
Students will able to
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Course |
Learning outcomes (at course level |
Learning and teaching strategies |
Assessment Strategies
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Paper Code |
Paper Title |
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STT-225 |
Practical |
CO 46: Analyze statistical measures such as Covariance, correlation coefficient, rank correlation for bivariate data.
CO 47: Calculation, Interpretation and application of Correlation and Regression Analysis.
CO 48: Deal with the problems of partial and multiple correlations
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Approach in teaching: Interactive Lectures, Group Discussion, Classroom Assignment Problem Solving Sessions
Learning activities for the students: Assignments Seminar Presentation Subject based Activities |
Software based Assignments Individual Presentation Class Test |
1. Correlation and regression(multiple and partial)
2.One-way classified data
3. Two way classification with single and equal observations
4. Two way classification with unequal observations
5. Analysis of BIBD.
6. Yates method for analysis 2nfactorial experiments : n=2,3,4
7. Total confounding in 2 n, n = 3, 4
8. Partial confounding in 2n, n = 3, 4
9. 32factorial experiments
10. Analysis of covariance in one way classified data and two way classified data
11. Analysis of RBD, LSD with one and two missing observations.
12. Drawing of random samples from finite populations.
13. Estimation of population mean and estimation of variance in SRS with and without replacement.
14. Estimation of mean and variance in stratified sampling under proportional and optimum allocations.
15. Gain in precision due to stratification.
16. Estimation of mean and variance in systematic sampling and comparison with S.R.S.
17. Estimation of mean and variance in cluster sampling and comparison with S.R.S.
18. PPSWR Sampling: Cumulative total method, Lahri's method of sample selection/section , estimation of total and its variance.
19. Estimation of mean and variance by (i) ratio and (ii) regression methods of estimation.
20. Two-stage sampling method where f.s.u. being selected with pps with replacement and s.s.u. with equal prob. without replacement . Estimation of optimum number of s.u. and s.s.u.
Note: Practical exercises will be conducted on computer by using MS-Excel/ SPSS/R.
