Probability Methods in Engineering I

Lecturer:

Gejza Dohnal

Tutor:

Gejza Dohnal

Supervisor:

Department of Technical Mathematics

Synopsis:

Advanced course of probability theory, involves such notions as probability space, random variable, random vector and its probability characteristics and distributions, limit theorems. In the second part, the basic principles of statistical inference will be treated.

Requirements:

Syllabus of lectures:

1 Classical definition of probability, probability space

2 Random variable, probability distribution

3 Probability characteristics of random variable

4 Discrete and continuous models

5 Random vector, characteristics

6 Distribution of transformed variable

7 Law of large numbers, central limit theorems

8 Statistical inference

9 Basic sample characteristics

10 Point and interval estimation. Methods of construction

11 Testing of statistical hypothesis.

12 Nonparametric tests, goodness-of-fit tests

13 ANOVA

14 Regression model, analysis of residuals

Syllabus of tutorials:

1 Classical definition of probability, probability space

2 Random variable, probability distribution

3 Probability characteristics of random variable

4 Discrete and continuous models

5 Random vector, characteristics

6 Distribution of transformed variable

7 Law of large numbers, central limit theorems

8 Statistical inference

9 Basic sample characteristics

10 Point and interval estimation.

Methods of construction

11 Testing of statistical hypothesis.

12 Nonparametric tests, goodness-of-fit tests

13 ANOVA

14 Regression model, analysis of residuals

Study Objective:

Study materials:

Mukhopadhyay N.: Probability and statistical inference. M. Dekker Inc., 2001.

Note:

Time-table for winter semester 2011/2012:

Time-table is not available yet

Time-table for summer semester 2011/2012:

Time-table is not available yet

The course is a part of the following study plans: