151-0333/01 – Statistics G (Stat G)
| Gurantor department | Department of Mathematical Methods in Economics | Credits | 5 |
| Subject guarantor | prof. RNDr. Dana Šalounová, Ph.D. | Subject version guarantor | prof. RNDr. Dana Šalounová, Ph.D. |
| Study level | undergraduate or graduate | Requirement | Compulsory |
| Year | 2 | Semester | winter |
| | Study language | Czech |
| Year of introduction | 2012/2013 | Year of cancellation | 2022/2023 |
| Intended for the faculties | EKF | Intended for study types | Bachelor |
Subject aims expressed by acquired skills and competences
The aim is
-t o learn students how to present a set of data by tables, graphs and descriptive measures,
- to make them acquainted with some parts of probability theory, especially with the term random variable, that is one of tools for description of uncertainity of real economical situations,
- to make them able to use basic types of probability distributions for solution of practical cases,
- to make them know the principles of some methods of statistical inference and use them for estimating and testing population parameters,
- to give the view of regression and correlation analysis.
Teaching methods
Lectures
Tutorials
Summary
1. An algebra of events.
Events, outcomes, the complement of an outcome. Operations over events.
2. Introduction to probability.
The addition law. Mutually exclusive events, conditional probability, independent events, the multiplication law. Bayes´ theorem.
3. Discrete random variables. Summary of discrete probability distributions.
4. Continuous random variables. Summary of continuous probability distributions.
5. Special cases of continuous distributions. Limit theorems.
6. Data, measurment. Summarizing data, graphs.
7. Numerical descriptive statistics. Measures of location.
8. Measures of dispersion.
9. Characteristics of shape of data sets.
10. Bivariate data, correlation coefficient.
11. Simple linear regression.
12. Populations, samples, statistical inference - preview.
13. Estimations. Point estimators, interval estimation of population characteristics.
14. Hypothesis testing - principles.
Compulsory literature:
Teaching material of respective teachers.
Recommended literature:
Way of continuous check of knowledge in the course of semester
Zápočet:
- aktivní účast na cvičeních,
- zápočtová písemka během semestru (max. 30 bodů),
- vypracování a včasné odevzdání projektu (max. 15 bodů).
Minimální počet bodů k udělení zápočtu: 23 bodů.
Podmínky pro individuální studijní plán: Totéž, účast ve cvičeních je možno nahradit vypracováním úloh zadaných vyučujícím.
E-learning
Other requirements
Zápočet:
- aktivní účast na cvičeních,
- zápočtová písemka během semestru (max. 30 bodů),
- vypracování a včasné odevzdání projektu (max. 15 bodů).
Minimální počet bodů k udělení zápočtu: 23 bodů.
Podmínky pro individuální studijní plán: Totéž, účast ve cvičeních je možno nahradit vypracováním úloh zadaných vyučujícím.
Prerequisities
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1. An algebra of events.
Events, outcomes, the complement of an outcome. Operations over events.
2. Introduction to probability.
The addition law. Mutually exclusive events, conditional probability, independent events, the multiplication law. Bayes´ theorem.
3. Discrete random variables. Summary of discrete probability distributions.
4. Continuous random variables. Summary of continuous probability distributions.
5. Special cases of continuous distributions. Limit theorems.
6. Data, measurment. Summarizing data, graphs.
7. Numerical descriptive statistics. Measures of location.
8. Measures of dispersion.
9. Characteristics of shape of data sets.
10. Bivariate data, correlation coefficient.
11. Simple linear regression.
12. Populations, samples, statistical inference - preview.
13. Estimations. Point estimators, interval estimation of population characteristics.
14. Hypothesis testing - principles.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction