SubjectsSubjects(version: 955)
Course, academic year 2023/2024
Statistics 2 - B501014
Title: Statistika 2
Guaranteed by: Department of Economics and Management (837)
Faculty: Central University Departments of UCT Prague
Actual: from 2023
Semester: both
Points: 6
E-Credits: 6
Examination process:
Hours per week, examination: 2/2, C+Ex [HT]
Capacity: winter:unknown / unknown (unknown)
summer:unknown / unknown (unknown)
Min. number of students: unlimited
State of the course: taught
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Note: course can be enrolled in outside the study plan
enabled for web enrollment
you can enroll for the course in winter and in summer semester
Guarantor: Koťátková Stránská Pavla Ing. Ph.D.
Interchangeability : AB501014
This subject contains the following additional online materials
Annotation -
The Statistics 2 course introduces other basic statistical procedures in working with data, especially in their analysis, and aims at their application to real problems of economic practice. It is based on a theoretical and methodological background with the aim of qualified interpretation of the results obtained and verification of established statistical hypotheses or questions. The tools of statistical analysis will be theoretically laid out with the practical application being carried out using selected statistical software, e.g. MS Excel, Gretl, Statistika.
Last update: Koťátková Stránská Pavla (12.09.2023)
Literature -

Z: Budíková, M., Králová, M., Maroš, B. (2010). Průvodce statistickými metodami. Praha: Grada Publishing.

Z: HENDL, J. (2004), Přehled statistických metod zpracování dat, Praha, Portál. ISBN 80-7178-820-1

Z: KOŽÍŠEK, J., STIEBEROVÁ, B.(2012), Statistika v příkladech, Verlag Dashofer.

D: ANDĚL, J. (2002), Základy matematické statistiky, Univerzita Karlova v Praze, Matematicko-fyzikální fakulta, Preprint.

D: HINDLS, R., HRONOVÁ, S. et al. Statistika pro ekonomy. Professional publishing. 2007. ISBN 978-80-86946-43-6.

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

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

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

Last update: Koťátková Stránská Pavla (12.09.2023)
Requirements to the exam -

The written exam is used to check whether the student has understood the material and can choose a statistical tool or model to solve the problem. The student applies for the exam through the student information system and is conditional on receiving credit. The examination is written or may be supplemented by an oral examination.

Last update: Koťátková Stránská Pavla (12.09.2023)
Syllabus -

1. Repetition of the basics of statistics I Random variable and probability. Probability distributions. All in practice.

2. Repetition of the basics of statistics II. Descriptive statistics. Statistical inference - point and interval estimates. Hypothesis testing, basic parametric tests (equality of mean, variance, etc.). All in practice.

3. Repetition of the basics of statistics III. Basic non-parametric tests: Mann-Whitney, Wilcoxon rank-sum, sign test, etc.

4. Normal distribution and its importance. Standard tests of normality: Pearson Chi-squared test, Shapiro-Wilk test, Kolmogorov-Smirnov test.

5. Categorical data. Importance, interpretation, representation, analysis.

6. Association between ordinal and nominal variables. Contingency tables, Pearson Chi-squared test as test of independence.

7. Introduction to analysis of variance. Assumptions for 1-way ANOVA. Non-parametric one-way ANOVA (Kruskal-Wallis test). Multiple comparison.

8. Correlation analysis I. Graphical methods, Pearson and Spearman correlation coefficient. Tests of significance.

9. Correlation analysis for non-normal data: biserial and tetrachoric correlation.

10. Correlation analysis III. Multivariate correlation: pair, multiple, partial correlation.

11. Introduction to Regression analysis I. Correlation vs. causality. Simple linear regression model, tests of significance of coefficients, F-test, coefficient of determination. LRM in Gretl.

12. Introduction to Regression analysis II. Nonlinearities in simple regression model (logarithmic transformations, polynomials). Evaluating and interpreting the results, possible problems.

13. Methods of multivariate analysis. Cluster analysis, factor analysis, principal component analysis. Applications in marketing.

14. Final recap, consultations.

Last update: Koťátková Stránská Pavla (12.09.2023)
Course completion requirements -

Minimum active participation in the exercise of 75%,

If the student does not reach the minimum requirement, an individual seminar paper will be assigned, which will be accepted and graded based on pre-determined rules.

Active participation in the exercises also includes work in e-learning - course Statistics II, i.e. work with materials + passing The credit test will include mainly examples, partly theory. The minimum threshold for passing the credit test is 50%. In case of failure, it is possible to repeat the credit test.

The exam is divided into two parts: written and oral. It will verify the understood material from lectures and study materials and practical verification of theoretical knowledge in calculations and in practice.

Last update: Koťátková Stránská Pavla (12.09.2023)
Teaching methods
Activity Credits Hours
Obhajoba individuálního projektu 0.1 4
Účast na přednáškách 1 28
Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi 1.4 40
Práce na individuálním projektu 1.3 36
Příprava na zkoušku a její absolvování 1.1 32
Účast na seminářích 1 28
6 / 6 168 / 168
Coursework assessment
Form Significance
Examination test 80
Continuous assessment of study performance and course -credit tests 20