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Practical [1]

Paper Code: 
CSTT 302
Credits: 
2
Contact Hours: 
60.00
Max. Marks: 
100.00
Objective: 

This paper is designed so that the student gets familiar with statistical software for solving the statistical problems based on Large sample test, Small sample test and Statistical Inference.

 

Students will be able to:

Course

Learning outcomes (at course level

Learning and teaching strategies

Assessment Strategies

Paper Code

Paper Title

CSTT 302

Practical

 

CO 26: Use Cramer-Rao inequality to derive the lower bound for the variance of an unbiased estimator and evaluate its efficiency.

 

 CO 27: Solve problems related to numeric and statistical data offline.

 

CO 28:  Apply the hypothesis on testing of attributes. 

 

CO 29: Apply small sample tests for mean and variation for one and two sample problems

 

CO 30: Use maximum likelihood estimation to obtain the point estimates and confidence intervals for unknown parameters in various models.

Approach in teaching:

 

Interactive Lectures,

Group Discussion,

Classroom Assignment

Problem Solving Sessions

 

 

Learning activities for the students:

 

Assignments

Seminar

Presentation

Subject based  Activities

Classroom Quiz

Assignments

Class Test

Individual Presentation

 

 

 

  1. Problems on properties of good estimator
  2. Chi-square test for homogeneity of population variance.
  3. Chi-square test for goodness of fit.
  4. Chi- square test for independence of Attributes.
  5. t-test for single mean
  6. t-test for difference of means (paired and unpaired cases)
  7. t- test for correlation coefficient.
  8. F-test for equality of population variances.
  9. Question based on CR inequality 
  10. Questions on MLE.

Note: Practical exercises will be conducted on the computer by using SPSS.

Academic Year: 
2023-2024 [2]

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Source URL: https://www.statistics.iisuniv.ac.in/courses/subjects/practical-80

Links:
[1] https://www.statistics.iisuniv.ac.in/courses/subjects/practical-80
[2] https://www.statistics.iisuniv.ac.in/academic-year/2023-2024