VŠTE:BSA_STA Statistics - Course Information

BSA_STA Statistics

Extent and Intensity

2/2/0. 5 credit(s). Type of Completion: zk (examination).

Teacher(s)

Ing. Josef Šedivý (seminar tutor)
Ing. Martin Telecký, Ph.D. (seminar tutor)

Guaranteed by

Ing. Martin Telecký, Ph.D.
Department of Informatics and Natural Sciences – Faculty of Technology – Rector – Institute of Technology and Business in České Budějovice
Supplier department: Department of Informatics and Natural Sciences – Faculty of Technology – Rector – Institute of Technology and Business in České Budějovice

Timetable of Seminar Groups

BSA_STA/A4: Sat 2. 11. 9:40–11:10 B1, 11:25–12:55 B1, 13:05–14:35 B1, 14:50–16:20 B1, Sun 1. 12. 9:40–11:10 B2, 11:25–12:55 B2, 13:05–14:35 B2, 14:50–16:20 B2, J. Šedivý
BSA_STA/P01: Mon 9:40–11:10 E6, J. Šedivý
BSA_STA/S16a: Mon 14:50–16:20 D316, J. Šedivý
BSA_STA/S16b: Tue 9:40–11:10 D216, J. Šedivý

Course Enrolment Limitations

The course is offered to students of any study field.

Course objectives supported by learning outcomes

The aim of the course is to acquaint students with basic and practical econometric methods of qualitative and quantitative analysis characters and with time series analysis elements.

Learning outcomes

After completing the course, the student can: 1. use basic procedures in the field of statistical induction 2. can characterize and apply methods of analysis of qualitative features 3. can characterize and apply methods of analysis and quantitative characters 4. can characterize the elements of time series analysis 5. can collect, sort, process and present econometric data

Syllabus

• Lectures: 1. Statistics, economics, econometrics, economic statistics: basic concepts, stages of statistical research, distribution table frequencies, statistical graphs. 2. Basic statistical characteristics: interpretation of the arithmetic mean and median, variance and standard deviations, variational coefficient, percentiles, characteristics for aggregated data, 8 simple and complex indexes for tracking national economy, industry and companies. 3. Gaussian curve - its explanation and application: random variable a its probability distribution, mean and random variance quantities. 4. Null hypotheses - explanation and application: most often used test criteria, test significance level, critical test value. 5. Two-sample tests: test of differences between two groups or pairs. 6. PivotTable tests: testing the independence between monitored characters in the PivotTable. 7. Simple linear regression: regression line, rules for so-called BLUE estimate, correlation coefficient. 8. Interpretation of coefficients in regression model: logarithmic transformations, tests in regression analysis. 9. Multidimensional regression: rules for so-called BLUE estimation, regression coefficients and their interpretation, coefficient of determination, tests on the significance of the model. 10. Time series: characteristics of time series, rules for BLUE estimate. 11. Time series: simple BLUE regression models. 12. Panel data: characteristics of panel data estimation, fixed effects and a random time series effect. 13. New trends and methods in econometrics: business economics, finance, micro-economics and macro-economics. Seminars: 1. Creating histograms and graphs to display different types of data. 2. Interpretation of arithmetic mean, median, variance a standard deviations, coefficient of variation, percentile. 3. Creation and interpretation of simple and complex indices for monitoring of the national economy, industry and companies. 4. Application of Gaussian curve and testing of null hypotheses o normalcy. 5. Parametric tests of difference between two groups or pairs. 6. Nonparametric tests of difference between two groups or pairs. 7. Testing the independence between the observed characters in contingency table. 8. Interpretation of coefficients in a simple regression model, diagnostics of estimation and its interpretation. 9. Interpretation, coefficients in multiple regression model, diagnostics of estimation and its interpretation. 10. Creation of questionnaires for established hypotheses: examples of good practice. 11. Application of simple regression models for time series, diagnostics of estimation and its interpretation. 12. Simple estimation of panel data using fixed effects. 13. Simple estimation of panel data using a random effect.

Literature

required literature
• ADAMEC, V., L. STŘELEC a D. HAMPEL, 2017. Ekonometrie I: učební text. Druhé nezměněné vydání. Brno: Mendelova univerzita v Brně. ISBN 978-80-7509-480-3.
• HINDLS, R., 2018. Statistika v ekonomii. [Průhonice]: Professional Publishing. ISBN 978-80-88260-09-7.
• MOŠNA, F., 2017. Základní statistické metody. Praha: Univerzita Karlova v Praze - Pedagogická fakulta. ISBN 978-80-7290-972-8.
• BARROW, M. M., 2017. Statistics for Economics, Accounting and Business Studies. 7 edit. [s. l.]: Pearson, Harlow. ISBN 978-1292118703. MCCLAVE, J. T., P. G. BENSON a T. SINCICH, 2018. Statistics for Business and Economics. Global Edition, 13 edit. [s. l.

recommended literature
• ČECHURA, L. et al., 2013. Cvičení z ekonometrie. 3. vyd. Praha: Česká zemědělská univerzita, Provozně ekonomická fakulta. ISBN 978-80-213- 2405-3.
• ADAMEC, V. a L. STŘELEC, 2016. Ekonometrie I: cvičebnice. Třetí upravené vydání. Brno: Mendelova univerzita v Brně. ISBN 978-80- 7509-396-7.
• STUCHLÝ, J., 2015. Statistické analýzy dat. České Budějovice: Vysoká škola technická a ekonomická. ISBN 978-80-7468-087-8.
• ARLTOVÁ, M., 2014. Základy statistiky v příkladech. Brno: Tribun EU. ISBN 978-80-263-0756-3.

Forms of Teaching

Lecture
Seminar
Exercise
Tutorial
Consultation

Teaching Methods

Frontal Teaching
Group Teaching - Competition
Project Teaching
Brainstorming
Critical Thinking
Individual Work– Individual or Individualized Activity
Teaching Supported by Multimedia Technologies

Student Workload

Activities	Number of Hours of Study Workload
	Daily Study	Combined Study
Preparation for the Mid-term Test	10	10
Preparation for Seminars, Exercises, Tutorial	44	80
Preparation for the Final Test	20	20
Participation in a continuous test	2	2
Attendance on Lectures	26
Attendance on Seminars/Exercises/Tutorial/Excursion	26	16
Participation in the final test	2	2
Total:	130	130

Assessment Methods and Assesment Rate

Test – mid-term 30 %
Test – final 70 %

Exam conditions

To successfully complete the course, it is necessary to achieve a total of continuous and a final evaluation of at least 70% under the conditions set out below conditions. In the continuous evaluation, 30 points can be obtained, ie 30%. In the final evaluation, a total of 70 points can be obtained = 70%. Total subject classification, ie points for the final evaluation (70 - 0) + points from continuous assessment (30 - 0): A 100 - 90, B 89.99 - 84, C 83.99 - 77, D 76.99 - 73, E 72.99 - 70, FX 69.99 - 30, F 29.99 - 0. The student of the full-time form of study is obliged for contact teaching, ie everything in addition to lectures, meet the mandatory 70% attendance.

Language of instruction

Czech

Teacher's information

Attendance at classes in all forms is governed by a separate internal standard of VŠTE (Records of student attendance at VŠTE). For full-time students 70% attendance at seminars is mandatory.

• Enrolment Statistics (recent)
  
• Permalink: https://is.vstecb.cz/course/vste/winter2024/BSA_STA