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Details of MA4106 (Autumn 2024)

Level: 4 Type: Theory Credits: 4.0

Course CodeCourse NameInstructor(s)
MA4106 Statistics II Satyaki Mazumder

Preamble
This is a course with significant Lab component.

Syllabus
Simulation: Simulation technique for non-standard distributions including c2, t and F distributions (central as well as non-central).

Inference: MLE, drawbacks of method of moment estimation, EM algorithm, Estimation of linear model (with multicollinearity and multiple regression), exact tests for discrete and continuous (specially non-normal) distributions, interval estimation, c2 and KS goodness-of-fit test, frequency c2 and its use in testing of hypothesis (contingency table), test for r.

Prerequisite
Statistics I (MA3205)

References


  1. Casella, G. and Berger, R.L., Statistical Inference, Thomson Brooks/Cole.

  2. Friedman, J., Hastie, T. and Tibshirani, R., The Elements of Statistical Learning, Springer.

  3. Kundu, D. and Basu, A., Statistical Computing: Existing Results and Recent Trends, Narosa Publishing House.

  4. Ross, S.M., Introduction to Probability Models, Elsevier.

Course Credit Options

Sl. No.ProgrammeSemester NoCourse Choice
1 IP 1 Not Allowed
2 IP 3 Not Allowed
3 IP 5 Not Allowed
4 MP 1 Not Allowed
5 MP 3 Not Allowed
6 MR 1 Not Allowed
7 MR 3 Not Allowed
8 MS 3 Not Allowed
9 MS 5 Not Allowed
10 MS 7 Elective
11 MS 9 Elective
12 RS 1 Elective
13 RS 2 Elective

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