VŠTE:B_STA Statistics - Course Information

B_STA Statistics

Extent and Intensity

2/4/0. 7 credit(s). Type of Completion: zk (examination).

Teacher(s)

Ing. Monika Burghauserová (seminar tutor)
Ing. Yelyzaveta Shebalkova (seminar tutor)
Ing. Josef Šedivý, Ph.D. (seminar tutor)
prof. Ing. Marek Vochozka, MBA, Ph.D., dr. h.c. (seminar tutor)

Guaranteed by

Robin Kunju Mol Raj, MBA, PhD.
Department of Corporate Finance and Economics – School of Expertness and Valuation – Rector – Institute of Technology and Business in České Budějovice
Supplier department: Department of Corporate Finance and Economics – School of Expertness and Valuation – Rector – Institute of Technology and Business in České Budějovice

Timetable of Seminar Groups

B_STA/K01: Sun 25. 10. 16:30–18:00 D316, Sat 7. 11. 8:00–12:30 D316, Sat 14. 11. 13:05–17:35 D316, Sun 22. 11. 13:05–17:35 D316, Sun 6. 12. 11:25–14:25 D316, M. Burghauserová
B_STA/P01: Mon 8:00–9:30 I201, M. Vochozka
B_STA/S01: Wed 11:25–12:55 D316, Fri 9:40–11:10 D316, Y. Shebalkova
B_STA/S02: Mon 14:50–16:20 D316, Thu 14:50–16:20 D316, M. Burghauserová

Prerequisites (in Czech)

B_MAT_2 Mathematics II || MAT_2z Mathematics II && INF_2z Informatics II || B_INF_2 Informatics II

Course Enrolment Limitations

The course is only offered to the students of the study fields the course is directly associated with.

fields of study / plans the course is directly associated with

there are 12 fields of study the course is directly associated with, display

Course objectives supported by learning outcomes

The aim of the course is to acquaint students with the basic procedures in the field of statistical induction, methods of analysis of qualitative and quantitative features and with the elements of time series analysis. After completing the course, the student is able to define the basic procedures in the field of statistical induction, can characterize and apply methods of analysis of qualitative and quantitative features and elements of time series analysis. The graduate is able to collect, sort, process and present statistical data.

Learning outcomes

After the successful completion of the course, the student masters the basic procedures in the field of statistical induction, methods of analysis of qualitative and quantitative features and with time series analysis elements. The student is able to collect, process and present statistical data.

Syllabus

1. Methods of descriptive statistics. 2. Basic statistical characteristics and indices. 3. Probability and distribution of probabilities and their numerical characteristics. 4. Basic probability models. 5. Sample surveys, distribution of sampling characteristics and basics of statistical induction. 6. Testing statistical hypotheses. 7. Two-sample tests. 8. Further tests and analysis of variance. 9. Simple linear regression and correlation. 10. Statistical induction in regression model. 11. Multidimensional regression and prognostic application of regression. 12-13. Introduction to time series analysis.

Literature

required literature
• VOCHOZKA, M. a Y. SHEBALKOVA, 2026. Statistika: studijní materiály. České Budějovice: Vysoká škola technická a ekonomická v Českých Budějovicích. ISBN 978-80-7468-217-9.
• VOCHOZKA, M. a Y. SHEBALKOVA, 2026. Cvičebnice statistiky: souhrnné vydání. České Budějovice: Vysoká škola technická a ekonomická v Českých Budějovicích. ISBN 978-80-7468-215-5.

recommended literature
• VOCHOZKA, M. and Y. SHEBALKOVA, 2026. Statistics: study text. České Budějovice: Institute of Technology and Business in České Budějovice. ISBN 978-80-7468-216-2.
• NEUBAUER, J., M. SEDLAČÍK a O. KŘÍŽ, 2021. Základy statistiky: aplikace v technických a ekonomických oborech. 3., rozšířené vydání. Praha: Grada. ISBN 978-80-271-3421-2.
• VOCHOZKA, M. and Y. SHEBALKOVA, 2026. Workbook of exercises in statistics: complete edition. České Budějovice: Institute of Technology and Business in České Budějovice. ISBN 978-80-7468-214-8.
• CAMM, J. D., J. J. COCHRAN, M. J. FRY, J. W. OHLMANN, D. R. ANDERSON, D. J. SWEENEY and T. A. WILLIAMS, 2024. Statistics for Business & Economics. 15th ed. Boston: Cengage Learning. ISBN 978-0-357-71585-7.

Organizační formy výuky

Lecture
Seminar
Exercise
Excursion - language
Tutorial
Consultation
Teaching Block - tutorial

Komplexní výukové metody

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

Student Workload

Activities	Number of Hours of Study Workload
	Daily Study	Combined Study
Preparation for the Mid-term Test	26	26
Preparation for Lectures	5
Preparation for Seminars, Exercises, Tutorial	23	50
Preparation for the Final Test	50	54
Attendance on Lectures	26
Attendance on Seminars/Exercises/Tutorial/Excursion	52	52
Total:	182	182

Metody hodnocení a jejich poměr

Test – mid-term 30%
Test – final 70%

Podmínky testu

Full-time study: 1) 2x Continuous test of 15 points each - a total of 30 possible points. 2) Final test – 70 points. Combined Studies: 1) Practice test for 100 points. The overall classification of the subject, i.e. the body for the test (70 - 0) + the body from  continuous tests (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. You need a minimum of 70 points to complete the subject

Language of instruction

Czech

Teacher's information

Attendance in lessons is defined in a separate internal standard of ITB (Evidence of attendance of students at ITB). It is compulsory, except of the lectures, for full-time students to attend 70 % lesson of the subjet in a semester.

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