151-0503/04 – Statistics A (StatA)
| Gurantor department | Department of Mathematical Methods in Economics | Credits | 5 |
| Subject guarantor | doc. Ing. Václav Friedrich, Ph.D. | Subject version guarantor | doc. Ing. Václav Friedrich, Ph.D. |
| Study level | undergraduate or graduate | Requirement | Choice-compulsory |
| Year | 1 | Semester | summer |
| | Study language | English |
| Year of introduction | 2011/2012 | 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
-to 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
Předmět představuje vstupní kurs do problematiky pravděpodobnosti a
statistiky. Poskytuje základy k dovednosti popisovat náhodné procesy v
ekonomii pomocí náhodných proměnných. Seznamuje se základy deskriptivní statistiky, statistické indukce, regresní analýzy, korelační analýzy.
Compulsory literature:
Teaching material of respective teachers.
Recommended literature:
Way of continuous check of knowledge in the course of semester
Lectures
Tutorials
Tests
Exam
E-learning
Other requirements
Lectures
Tutorials
Tests
Exam
Prerequisities
Subject has no 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