SubjectsSubjects(version: 893)
Course, academic year 2021/2022
Statistics 2 - AB501014
Title: Statistics 2
Guaranteed by: Department of Economics and Management (837)
Actual: from 2020
Semester: summer
Points: summer s.:6
E-Credits: summer s.:6
Examination process: summer s.:
Hours per week, examination: summer s.:2/2 C+Ex [hours/week]
Capacity: unknown / unknown (unknown)
Min. number of students: unlimited
Language: English
Teaching methods: full-time
For type: Bachelor's
Note: course can be enrolled in outside the study plan
enabled for web enrollment
Guarantor: Koťátková Stránská Pavla Ing. Ph.D.
Is interchangeable with: B501014
Examination dates   Schedule   
This subject contains the following additional online materials
Literature -
Last update: Krajčová Jana Mgr. Ph.D., M.A. (08.02.2021)

R: LIND, D., MARCHAL, W., WATHEN, S. Statistical Techniques in Business and Economics, (16th Edition). McGraw-Hill Education 2015. ISBN-13: 978-0078020520.

R: TRIOLA, M., F. Essentials of Statistics (5th Edition). Pearson Education 2015. ISBN-13: 978-0321924599.

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

R: STUDENMUND, A.H. Using econometrics: A practical guide. New York: Pearson Global Edition, 2017. ISBN: 978-01-3136773-9.

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

A: SALKIND, N.J. Excel Statistics. Sage Publications, 2015.

Last update: Botek Marek Mgr. Ing. Ph.D. (17.01.2020)

1. Basic statistics and probability – review

2. Basic parametric tests

3. Basic non-parametric tests

4. Normality test - Chi squared test, Shapiro-Wilk test, Kolmogorov-Smirnov test

5. Categorical variable – analysis

6. Association between ordinal and nominal variables– contingency table, chi squared test of independence

7. Analysis of variance I – one -way ANOVA a Kruskal Walis test

8. Correlation analysis - graphical methods, Person and Spearman correlation coefficient

9. Correlation analysis – biserial and tetrachoric correlation

10. Correlation analysis (multivariate) - multiple and partial correlation

11. Methods of multivariate analysis - cluster analysis, factor analysis, principal component analysis

12. Regression analysis I - simple linear regression model, tests of significance of coefficients, F-test, coefficient of determination

13. Regression analysis II - nonlinearities in simple regression model (logarithmic transformations, polynomials)

14. Final recap

Course completion requirements -
Last update: Botek Marek Mgr. Ing. Ph.D. (17.01.2020)

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.