Introduction to Probability 2

Course guarantor:

Jiří Franc

Lecturer:

Tutor:

Supervisor:

Department of Mathematics

Synopsis:

1. One-dimensional continuous random variable and its statistical description.

2. Distribution function and probability density.

3. Axiomatic introduction of probability and connection to measure theory.

4. Numerical characteristics of continuous random variables.

5. Selected variants of continuous distributions and their characteristics.

6. Elementary methods for point estimations.

7. Generating pseudorandom numbers from the selected distribution.

Requirements:

Syllabus of lectures:

1. One-dimensional continuous random variable and its statistical description.

2. Distribution function and probability density.

3. Axiomatic introduction of probability and connection to measure theory.

4. Numerical characteristics of continuous random variables.

5. Selected variants of continuous distributions and their characteristics.

6. Elementary methods for point estimations.

7. Generating pseudorandom numbers from the selected distribution.

Syllabus of tutorials:

Study Objective:

Study materials:

Key references:

[1] Jacod, J., Protter, P.: Probability Essentials, Springer, New York, 2004.

[2] Pishro-Nik, H.: Introduction to Probability, Statistics, and Random Processes. Kappa Research, LLC, 2014.

[3] Tucker, H. G.: Probability and Mathematical Statistics. Academic Press, London 1963.

Recommended references:

[4] Lehmann, E. L., Casella, G.: Theory of Point Estimation, 2nd Ed., Springer-Verlag, New York, 1998.

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans: