Details of ID4105 (Autumn 2015)

Level: 4 Type: Theory Credits: 3.0

Course CodeCourse NameInstructor(s)
ID4105 Mathematical Statistics I Asok Kumar Nanda

Syllabus
ID 4107 : Mathematical Statistics I



Review of probability distributions and mathematical expectation; multinomial and multivariate hypergeometric distributions; uniform, exponential and gamma distributions; normal approximation to binomial; bivariate normal distribution; distribution of functions of random variables; distribution of sample correlation coefficient when population correlation is zero; large sample distributions of sample quantiles; variance stabilizing transformation; Fishers z transformation; chi-square, t and F distributions (derivation of non-central distributions not needed); chi-square goodness-of-fit test, frequency chi-square and its use in testing of hypothesis (contingency table), distribution of multiple and partial correlation coefficients; multicollinearity, heteroscedasticity and autocorrelation in connection with multiple regression; some nonparametric tests.

References
Suggested Texts/Reference Books:



1. Cramer, H., Mathematical Methods of Statistics, Princeton University Press, 1999.

2. Mood, A., Graybill, F. A. and Boes, D. C., Introduction to the Theory of Statistics (3rd Edition), Mcgraw Hill, 1974.

3. Shao, J., Mathematical Statistics (2nd Edition), Springer, 2003.

4. Rao, C. R., Linear Statistical Inference and Its Applications (2nd Edition), Wiley-Interscience, 2001.

5. Wilks, S. S., Mathematical Statistics, Buck Press, 2008.





Course Credit Options

Sl. No.ProgrammeSemester NoCourse Choice
1 IP 1 Core
2 IP 3 Not Allowed
3 IP 5 Not Allowed
4 MR 1 Not Allowed
5 MR 3 Not Allowed
6 MS 7 Elective
7 RS 1 Not Allowed
8 RS 2 Elective