Practical

Paper Code: 
STT 225
Credits: 
4
Contact Hours: 
120.00
Max. Marks: 
100.00
Objective: 

Objective: 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

Course

Learning outcomes (at course level

Learning and teaching strategies

Assessment Strategies

 

Paper Code

Paper Title

STT-225

Practical

CO 51:  Identify the behaviour of the experimental unit and recognize issues of non-independence.

 

CO 52: Construct the design and deal with the problems of real world situations.

 

 

CO 53: Learn how a factorial design allows cost reduction, increases efficiency of experimentation.

 

CO 54: Apply various sampling designs such as simple, stratified, systematic, cluster and double sampling in real-life surveys.

 

 

 

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.

Academic Year: