CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2020/2021

# Probability and Statistics

Code Completion Credits Range
B0B01PST Z,ZK 7 4P+2S
Lecturer:
Mirko Navara (guarantor)
Tutor:
Mirko Navara (guarantor), Miroslav Korbelář, Matěj Novotný, Milan Petrík
Supervisor:
Department of Mathematics
Synopsis:

Basics of probability theory and mathematical statistics. Includes descriptions of probability, random variables and their distributions, characteristics and operations with random variables. Basics of mathematical statistics: Point and interval estimates, methods of parameters estimation and hypotheses testing, least squares method. Basic notions and results of the theory of Markov chains.

Requirements:

Linear Algebra, Calculus, Discrete Mathematics

Syllabus of lectures:

1. Basic notions of probability theory. Kolmogorov model of probability. Independence, conditional probability, Bayes formula.

2. Random variables and their description. Random vector. Probability distribution function.

3. Quantile function. Mixture of random variables.

4. Characteristics of random variables and their properties. Operations with random variables. Basic types of distributions.

5. Characteristics of random vectors. Covariance, correlation. Chebyshev inequality. Law of large numbers. Central limit theorem.

6. Basic notions of statistics. Sample mean, sample variance. Interval estimates of mean and variance.

7. Method of moments, method of maximum likelihood. EM algorithm.

8. Hypotheses testing. Tests of mean and variance.

9. Goodness-of-fit tests.

10. Tests of correlation, non-parametic tests.

11. Discrete random processes. Stationary processes. Markov chains.

12. Classification of states of Markov chains.

13. Asymptotic properties of Markov chains. Overview of applications.

Syllabus of tutorials:

1. Elementary probability.

2. Kolmogorov model of probability. Independence, conditional probability, Bayes formula.

3. Mixture of random variables.

4. Mean. Unary operations with random variables.

5. Dispersion (variance). Random vector, joint distribution. Binary operations with random variables.

6. Sample mean, sample variance. Chebyshev inequality. Central limit theorem.

7. Interval estimates of mean and variance.

8. Method of moments, method of maximum likelihood.

9. Hypotheses testing. Goodness-of-fit tests.

10. Tests of correlation. Non-parametic tests.

11. Discrete random processes. Stationary processes. Markov chains.

12. Classification of states of Markov chains.

13. Asymptotic properties of Markov chains.

Study Objective:

Basics of probability theory and their application in statistical estimates and tests.

The use of Markov chains in modeling.

Study materials:

[1] Wasserman, L.: All of Statistics: A Concise Course in Statistical Inference. Springer Texts in Statistics, Corr. 2nd printing, 2004.

[2] Papoulis, A., Pillai, S.U.: Probability, Random Variables, and Stochastic Processes. McGraw-Hill, Boston, USA, 4th edition, 2002.

[3] Mood, A.M., Graybill, F.A., Boes, D.C.: Introduction to the Theory of Statistics. 3rd ed., McGraw-Hill, 1974.

Note:
Further information:
http://cmp.felk.cvut.cz/~navara/stat/
Time-table for winter semester 2020/2021:
 06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00 roomT2:A4-204Petrík M.09:15–10:45(lecture parallel1parallel nr.105)DejviceUčebnaroomT2:A4-204Petrík M.12:45–14:15(lecture parallel1parallel nr.104)DejviceUčebnaroomT2:D3-209Navara M.14:30–16:00(lecture parallel1)DejviceT2:D3-209 roomT2:A4-204Petrík M.11:00–12:30(lecture parallel1parallel nr.106)DejviceUčebna roomT2:C3-337Navara M.09:15–10:45(lecture parallel1)DejviceT2:C3-337 roomKN:E-126Korbelář M.12:45–14:15(lecture parallel1parallel nr.101)Karlovo nám.Trnkova posluchárna K5roomKN:E-126Korbelář M.14:30–16:00(lecture parallel1parallel nr.102)Karlovo nám.Trnkova posluchárna K5roomKN:E-126Korbelář M.16:15–17:45(lecture parallel1parallel nr.103)Karlovo nám.Trnkova posluchárna K5
Time-table for summer semester 2020/2021:
Time-table is not available yet
The course is a part of the following study plans:
Data valid to 2020-10-27
For updated information see http://bilakniha.cvut.cz/en/predmet4681506.html