Probability and Statistics

Garant předmětu:

Pavel Hrabák

Přednášející:

Francesco Dolce, Pavel Hrabák

Cvičící:

Francesco Dolce

Předmět zajišťuje:

katedra aplikované matematiky

Anotace:

Students will learn the basics of probabilistic thinking, the ability to synthesize prior and posterior information and learn to work with random variables. They will be able to apply basic models of random variable distributions and solve applied probabilistic problems in informatics and computer science. Using the statistical induction they will be able to perform estimations of unknown distributional parameters from random sample characteristics. They will also be introduced to the methods for testing statistical hypotheses and determining the statistical dependence of two or more random variables.

Požadavky:

Basics of combinatorics and mathematical analysis.

Osnova přednášek:

1. Probability - random events, event space structure, probability of a random event and its basic properties.

2. Conditional probability - dependent and independent events, Bayes theorem.

3. Random variables - distribution function of a random variable, continuous and discrete distributions, quantiles, median.

4. Characteristics of random variables - expected value, variance, general moments, kurtosis and skewness.

5. Overview of basic distributions - binomial, geometric, Poisson, uniform, normal, exponential. Their basic properties.

6. Random vectors - joint and marginal statistics, correlation coefficient, dependence and independence of random variables.

7. Random vectors - conditional distributions, sums of random variables.

8. Limit theorems - laws of large numbers, central limit theorem.

9. Statistical estimation - classification and processing of data sets, graphical representation of data, random sample, point estimation, basic sample statistics, sample mean and variance.

10. Interval estimation - confidence intervals for expectation and variance.

11. Hypothesis testing - testing strategy, tests for expectation and variance, their modifications.

12. Application of statistical testing in computer science.

13. Correlation and regression analysis: Linear and quadratic regression, sample correlation.

Osnova cvičení:

1. Basics of probability.

2. Conditional probability.

3. Random variables.

4. Basic characteristics of random variables.

5. Using basic distributions.

6. Random vectors - independence, covariance.

7. Random vectors - conditional distributions and sums.

8. Limit theorems

9. Processing of sets of data.

10. Statistical point estimation.

11. Interval estimation.

12. Hypotheses testing.

13. Regression and correlation analysis.

Cíle studia:

The goal of the module is to introduce the students to basics of probability theory and mathematical statistics while focusing on applications in informatics.

Studijní materiály:

1. Ahn H. : Probability and Statistics for Science and Engineering with Examples in R. Cognella, 2017. ISBN 978-1516513987.

2. Johnson J. L. : Probability and Statistics for Computer Science. Wiley-Interscience, 2008. ISBN 470383429.

3. Bonselet Ch. : Probability, Statistics, and Random Signals. Oxford University Press, 2016. ISBN 978-0190200510.

4. Grimmett G. R., Stirzaker D. R. : Probability and Random Processes (3rd Edition). Oxford University Press, 2001. ISBN 0-19-857223-9.

Poznámka:

Chybí klíčvá slova a webová stránka.

Rozvrh na zimní semestr 2023/2024:

	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
Po	místnost TH:A-1442 Dolce F. 09:15–10:45 (přednášková par. 1) Thákurova 7 (budova FSv)místnost T9:347 Dolce F. 16:15–17:45 (přednášková par. 1 paralelka 101) Dejvice NBFIT učebna
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Rozvrh na letní semestr 2023/2024:

Rozvrh není připraven

Předmět je součástí následujících studijních plánů:

• Bachelor specialization, Computer Engineering, 2021 (povinný předmět programu)
• Bachelor specialization, Information Security, 2021 (povinný předmět programu)
• Bachelor specialization, Software Engineering, 2021 (povinný předmět programu)
• Bachelor specialization, Computer Science, 2021 (povinný předmět programu)
• Bachelor specialization, Computer Networks and Internet, 2021 (povinný předmět programu)
• Bachelor specialization Computer Systems and Virtualization, 2021 (povinný předmět programu)