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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2023/2024

Economic Statistics

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Code Completion Credits Range Language
126EKST Z,ZK 4 1P+2C Czech
Garant předmětu:
Daniel Macek
Lecturer:
Božena Kadeřábková, Daniel Macek
Tutor:
Daniel Macek
Supervisor:
Department of Construction Management and Economics
Synopsis:

The content of the subject is applied economic statistics. Familiarization with statistical theory and subsequent application to solved examples.

Requirements:

they are not

Syllabus of lectures:

1. Introduction to statistics, descriptive statistics

2. Hypothesis testing

3. Contingency analysis – contingency table, McNemar's test

4. Correlation analysis, One-factor analysis of variance - ANOVA

5. Regression analysis

6. Time series

7. Index analysis - basic and chain indices, individual and composite indices

Syllabus of tutorials:

1. Descriptive statistics – frequencies, measures of location and variability

2. Descriptive statistics – variance decomposition

3. Statistical hypothesis testing – relative frequency test, mean value test

4. Testing of statistical hypotheses – test of equality of mean values, test of dispersion

5. Statistical hypothesis testing – test of the agreement of two variances, Chi-square test of goodness of fit

6. Contingency analysis – contingency table, McNemar's test

7. One-factor analysis of variance - ANOVA

8. Correlation analysis – Pearson's correlation coefficient, Spearmen's order correlation coefficient

9. Regression analysis - linear regression

10. Regression analysis - regression parabola

11. Time series - descriptive characteristics, averages, measures of dynamics

12. Time series - analyses, seasonal components

13. Index analysis - basic and chain indices, individual and composite indices

Study Objective:

Orientation in the issue of economic statistics. Ability to use and interpret statistical analyzes from an economic point of view.

Study materials:

1. Descriptive statistics – frequencies, measures of location and variability

2. Descriptive statistics – variance decomposition

3. Statistical hypothesis testing – relative frequency test, mean value test

4. Testing of statistical hypotheses – test of equality of mean values, test of dispersion

5. Statistical hypothesis testing – test of the agreement of two variances, Chi-square test of goodness of fit

6. Contingency analysis – contingency table, McNemar's test

7. One-factor analysis of variance - ANOVA

8. Correlation analysis – Pearson's correlation coefficient, Spearmen's order correlation coefficient

9. Regression analysis - linear regression

10. Regression analysis - regression parabola

11. Time series - descriptive characteristics, averages, measures of dynamics

12. Time series - analyses, seasonal components

13. Index analysis - basic and chain indices, individual and composite indices

Note:
Time-table for winter semester 2023/2024:
06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon
roomTH:B-377

08:00–09:50
(lecture parallel1
parallel nr.103)

Thákurova 7 (budova FSv)
B377
Tue
roomTH:B-377

08:00–09:50
(lecture parallel1
parallel nr.101)

Thákurova 7 (budova FSv)
B377
roomTH:C-221

14:00–15:50
EVEN WEEK

(lecture parallel1)
Thákurova 7 (budova FSv)
C221
Wed
roomTH:B-377

12:00–13:50
(lecture parallel1
parallel nr.102)

Thákurova 7 (budova FSv)
B377
Thu
Fri
Time-table for summer semester 2023/2024:
Time-table is not available yet
The course is a part of the following study plans:
Data valid to 2024-04-17
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