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Practical
This paper is designed so that the student gets familiar with statistical software for solving the statistical problems based on design of experiment and sampling.
Students will be 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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DSTT 702(C)
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Practical |
CO 97: Develop the skills and knowledge required to design and analyze various experiments.
CO 98: Develop the ability to interpret the results obtained from the analysis and draw meaningful conclusions.
CO 99:Solve the samplings related problems and also do various comparisons between them.
CO 100: Estimate the mean and variance in SRS, Stratified, Systematic, and Cluster sampling, and evaluate their relative efficiencies. |
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
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- One-way, two way classified data with equal and unequal observations.
- Analysis of BIBD.
- Yates method for analysis 2^n factorial experiments: n=2,3,4.
- Partial and Total confounding in 2^n, n = 3, 4.
- 3^2 factorial experiments.
- Analysis of covariance in one way classified data and two way classified data.
- Estimation of mean and variance in Cluster sampling.
- PPSWR Sampling: Cumulative total method, Lahri’s method of sample selection/section, estimation of total and its variance.
Note: Practical exercises will be conducted on the computer by using MS-Excel.
