Mathematic Statistics 2

Lecturer:

Tutor:

Supervisor:

Department of Mathematics

Synopsis:

Advanced mathematical statistics with engineering applications

Requirements:

Syllabus of lectures:

1. Dependence and independence of random variables.

2. Contingency tables.

3. Linear model.

4. Analysis of variance.

5. Correlation analysis.

6. Analysis of principal components.

7. Logistic regression.

8. Time series analysis in time domain. Box-Jenkins metodology.

9. Time series in frequency domain - Fourier analysis.

Syllabus of tutorials:

Study Objective:

Study materials:

Jay L. Devore: Probability and Statistics for Engineering and the Sciences

Duxbury

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans: