Z: BUDÍKOVÁ, M., KRÁLOVÁ, M., MAROŠ, B. Průvodce statistickými metodami. Praha: Grada Publishing, 2010.

D: HEBÁK, P., HUSTOPECKÝ, J. Vícerozměrné statistické metody 1. Praha: Informatorium. 2006.

D: HEBÁK, P., HUSTOPECKÝ, J., MALÁ, I. Vícerozměrné statistické metody 2. Praha: Informatorium. 2005.

D: HINDLS, R. a kol. Statistika pro ekonomy. Praha: Profesional Publishing. 2007.

R: LIND, D., MARCHAL, W., WATHEN, S. (2015), Statistical Techniques in Business and Economics, (16th Edition). McGraw-Hill Education.

R: TRIOLA, M., F. (2015), Essentials of Statistics (5th Edition), Pearson Education.

R: LEVINE, SZABAT, STEPHAN (2016), Business Statistics: A First Course. New York: Pearson Global Edition.

R: ZÁŠKODNÝ, Přemysl (2012), The Principles of Probability and Statistics (Data Mining Approach). Praha: Curriculum.

Zápočet: aktivní účast na cvičeních, zpracování korespondenčních úkolů, závěrečné zápočtové písemné práce

Zkouška: písemná - část teoretická a část praktická

1. Introduction to statistics – types of data, surveys, data processing, representation of the data, graphs and tables

2. Descriptive statistics – central tendency and variability for the population and for the sample,

3. Descriptive statistics – measures of skewness and kurtosis, variance decomposition

4. One-dimensional discrete random variable – probability mass function, cumulative density function, selected discrete distributions

5. One-dimensional continuous random variable – probability density function, cumulative density function, selected discrete distributions

6. Random vectors – probability density function, cumulative density function, joint, marginal and conditional probability, independence, basic characteristics

7. Basics of probability theory - random variable, frequency, probability distribution and its main characteristics, probability function, density, distribution function and their basic properties

8. Statistical inference – population and a sample, point and interval estimates of mean and variance

9. Testing statistical hypotheses – null and alternative hypothesis, level of significance, critical values, rejection interval, type I and type II errors, p-value, one-sided and two-sided alternative hypothesis

10. Basic parametric tests - tests about mean (one-sample), tests about variance (one -sample)

11. Basic parametric tests - tests about mean (two-sample dependent and independent), tests about variance (two-sample)

12. Basic non-parametric tests - Mann-Whitney, Wilcoxon rank-sum

13. Basic non-parametric tests - sign test, Kolmogorov-Smirnov test etc.

14. Final recap

Zápočet: aktivní účast na cvičeních, zpracování korespondenčních úkolů, závěrečné zápočtové písemné práce

Zkouška: písemná - část teoretická a část praktická

Credit can be awarded to student based on his participation in practical exercises and submitted homework during the semester. Alternatively student can pass a test at the end of the semester, with minimum required score of 60%. The minimum required attendance rate to seminars is 75%. The details will be agreed upon with the seminar instructor at the beginning of the semester.

A credit is required to allow a student to take the final exam. The final exam will cover both, the theory and the practical exercises. The exam will be in written form but can be complemented by oral examination.