Cardinal Stefan Wyszynski University in Warsaw - Central Authentication System
Strona główna

Probability and statistics WM-I-RPS
Classes (CW) Winter semester 2021/22

Information on classes (common for all the groups)

Class hours: 30
Places limit: (no limit)
Bibliography:

1. Tikhonenko O., Tikhonenko A. Metody probabilistyczne. Wykłady i ćwiczenia dla informatyków. Oficyna Wyfawnicza EWSIE. Warszawa 2010

2. Krysicki W., Bartos J., Dyczka W., Królikowska K., Wasilewski M. Rachunek prawdopodobieństwa i statystyka matematyczna w zadaniach. Części 1, 2. PWN, Warszawa 1997

3. Plucińska A., Pluciński E. Zadania z rachunku prawdopodobieństwa i statystyki matematycznej dla studentów politechnik. PWN, Warszawa 1976

4. Stojanow J., Miraczijski I., Ignatow C., Tanuszew M. Zbiór zadań z rachunku prawdopodobieństwa. PWN, Warszawa 1991

Learning outcomes: (in Polish)

I1_U01, I1_U02, I1_U16

Assessment methods and assessment criteria: (in Polish)

Zaliczenie na podstawie ocen z kolokwiów.

List of topics:

1. Discrete probability space, combinatorics formulae, discrete uniform probability, sampling with replacement and without replacement. Bernoulli sequence.

2. General probability space, probability axiomatics. Probability properties.

3. Conditional probability. Events independence. Total probability. Bayes formula.

4. Random variables. Distribution and distribution function. Distribution function properties. Main distributions. Discrete and continuous random variables. Probability density.

5. Random variables numerical characteristics: expectation, variance, standard deviation, moments, correlation coefficient. Chebyshev inequality.

6. Multivariate random variables, random variables independence, joint distributions, conditional and marginal distributions

7. Types of covergence of random variable sequences: convergence in probability and convergence in distribution. Bernoulli, Chebyshev and Khinchyn laws of large numbers. Limits Theorems.

8. Colloquium.

9. Object of statistics. Sample method. Sample distribution function, histogram, sample moments and their properties.

10. Point estimation. Consistent, biased and unbiased estimators. Maximum likelihood and moments methods. Estimators comparison.

11. Main statistical distributions (chi-squqre, Student).

12. Interval estimation. Exact and asymptotic confidence intervals. Confidence intervals for normal distribution parameters.

13. Hypotheses testing. First kind and second kind error. Power of a statistical test. Parametrrical hypotheses testing. Criterion chi-square.

14. Nonparametric hypotheses testing: chi-square like nonparametric kriterion.

15. Colloquium.

Teaching methods: (in Polish)

Metoda ćwiczebna. Zajęcia na platformie MS Teams.

Class groups

see this on class schedule

Group Timeframe(s) Lecturers Places Number of students in group / places limit Actions
1 every Tuesday, 9:45 - 11:15, room e-learning
Oleg Tikhonenko 31/30 details
2 every Tuesday, 13:15 - 14:45, room e-learning
Oleg Tikhonenko 30/30 details
All lectures are taking place in this building:
(in Polish) e-learning
Course descriptions are protected by copyright.
Copyright by Cardinal Stefan Wyszynski University in Warsaw.
ul. Dewajtis 5,
01-815 Warszawa
tel: +48 22 561 88 00 https://uksw.edu.pl
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