# Statistical Methods I

- Credits: 8
- Ending: Examination
- Range: 2P + 2C
- Semester: summer
- Year: 1
- Faculty of Economic Informatics

## Teachers

## Included in study programs

**Teaching results**

After successful completion of this class, students will be able to make elementary statistical analyses based on descriptive statistics and statistical inference and will be able to interpret the results of these analyses correctly.

In particular, students will acquire the following abilities:

− Students will acquire knowledge about the descriptive statistics through which they will be able to describe properties of the statistical dataset.

− Students will acquire knowledge about the the theoretical distributions of statistical variables and about the principles of statistical inference.

− They will get acquainted with the principle of the one-way ANOVA and will acquire knowledge to verify the assumptions of ANOVA.

Students will acquire in particular the following skills:

− Students will be able to perform calculations for the relevant statistical procedures (descriptive statistics, statistical inference), both by their own calculations as well as with the use of a statistical software (e.g. SAS, Statgraphics).

− Students will learn to adequately interpret the results.

Students will acquire the following competencies:

− Students will be able to use the above stated knowledge and skills in solving practical tasks from economic practice.

**Indicative content**

The course Statistical methods I provides students with basic knowledge of two areas of statistics, namely descriptive statistics and statistical inference. In this course, students will acquire the knowledge and skills needed to understand other statistical (but also generally quantitative) methods and procedures.

**Support literature**

Labudová, V., Pacáková, V., Sipková, Ľ., Šoltés, E., Vojtková, M. (2021). Štatistické metódy pre ekonómov a manažérov. Bratislava: Iura Edition.

Šoltés, E. a kol. (2018). Štatistické metódy pre ekonómov – zbierka príkladov. Bratislava: Iura Edition.

Marek, L. a kol. (2007). Statistika pro ekonomy. Praha: Kamil Mařík – Professional Publishing.

Marek, L. a kol. (2015). Statistika v příkladech (2. vyd.). Praha: Kamil Mařík – Professional Publishing.

Johnson, R. A., Bhattacharyya, G. K. (2019). Statistics: principles and methods. John Wiley & Sons.

Literature will be continuously updated with the latest scientific and professional titles.

**Syllabus**

Syllabus: 1. Basic statistical terms. 2. Tabular and graphical presentation of statistical data. 3. Descriptive statistics (measures of location, measures of variability) 4. Descriptive statistics (measures of distribution shape) 5. Probability distributions. Sampling distributions. Central limit theorem. 6. Basic terms of statistical inference. Random sampling techniques. Point estimates and their properties. 7. Principle of interval estimates. Interval estimates of a population mean, variance and proportion. 8. Principle of hypothesis tests. Hypothesis tests about a population mean, variance and proportion. 9. Inferences about two population means, two variances and two proportions. 10. Analysis of variance (One-way ANOVA). 11. Assumptions for ANOVA. 12. Tests of Goodness of fit. 13. Summary.

**Requirements to complete the course**

30% assignments (2 assignments)

70% final exam (30% theoretical part, 40% practical part)

**Student workload**

Total study load (in hours): 208 hours

Distribution of study load

Lectures participation: 26 hours

Seminar participation: 26 hours

Preparation for seminars: 52 hours

Preparation for assignments: 52 hours

Preparation for final exam: 52 hours

**Language whose command is required to complete the course**

Slovak

Date of approval: 10.02.2023

Date of the latest change: 17.05.2022