ESF:BKM_STA2 Statistics 2 - Course Information
BKM_STA2 Statistics 2
Faculty of Economics and AdministrationSpring 2022
- Extent and Intensity
- 26/0/0. 5 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- Mgr. Lenka Zavadilová, Ph.D. (lecturer)
RNDr. Marie Budíková, Dr. (alternate examiner) - Guaranteed by
- doc. Mgr. Maria Králová, Ph.D.
Department of Applied Mathematics and Computer Science – Faculty of Economics and Administration
Contact Person: Lenka Hráčková
Supplier department: Department of Applied Mathematics and Computer Science – Faculty of Economics and Administration - Timetable
- Fri 25. 2. 12:00–15:50 P106, Fri 11. 3. 16:00–19:50 P106, Fri 6. 5. 16:00–19:50 P106
- Prerequisites
- ( BKM_STA1 Statistics I ) || ( BPM_STA1 Statistics 1 )
The basic terms in calculus of probability. - Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Non-profit-making Organization Economy and Management (programme ESF, B-HPS)
- Finance (programme ESF, B-FIN)
- Finance (programme ESF, B-FU)
- Management (programme ESF, B-EKM)
- Business Management (programme ESF, B-EKM)
- Business Management (programme ESF, B-PEM)
- Regional Development and Tourism (programme ESF, B-HPS)
- Regional Development and Tourism (programme ESF, B-RRCR)
- Regional Development and Administration (programme ESF, B-HPS)
- Regional Development and Administration (programme ESF, B-HPS, specialization Reg. Develop. & Admin.)
- Regional Development and Administration (programme ESF, B-HPS, specialization Reg. Develop. & Admin.)
- Public Economics and Administration (programme ESF, B-HPS)
- Public Economics and Administration (programme ESF, B-VES)
- Course objectives
- The goal of this course is to teach students the basic statistical techniques of real economic data analysis (with statsitical software)and to prepare them for additional statistical methods used in economy.
- Learning outcomes
- After graduation of the course student should be able to:
- distinguish between sample and population and properly interpret principles of inferential statistics
- determine statistical methods appropriate for particular application context
- solve tasks based on real data by means of sw. STATSTICA
- interpret properly outputs of analyses - Syllabus
- Basic concepts of mathematical statistics.
- Experiment design.
- Information about STATISTICA system.
- Diagnostics graphs and normality testing.
- One random normal and alternative sample exercises.
- Two independent random normal and alternative samples exercises.
- One-way ANOVA.
- Nonparametrics tests.
- Analysis of contingency tables.
- Correlation analysis. Regression analysis.
- Literature
- required literature
- BUDÍKOVÁ, Marie, Maria KRÁLOVÁ and Bohumil MAROŠ. Průvodce základními statistickými metodami (Guide to basic statistical methods). vydání první. Praha: Grada Publishing, a.s., 2010, 272 pp. edice Expert. ISBN 978-80-247-3243-5. URL info
- recommended literature
- BUDÍKOVÁ, Marie. Statistika II. 1. vyd. Brno: Masarykova univerzita v Brně, 2006, 156 s. ISBN 8021041056. info
- HINDLS, Richard, Stanislava HRONOVÁ and Jan SEGER. Statistika pro ekonomy. 1. vyd. Praha: Professional publishing, 2002, 415 s. ISBN 80-86419-26-6. info
- HENDL, Jan. Přehled statistických metod zpracování dat :analýza a metaanalýza dat. Vyd. 1. Praha: Portál, 2004, 583 s. ISBN 8071788201. info
- Teaching methods
- Theoretical lectures; computer seminar sessions.
- Assessment methods
- Distance study. Lectures, self study. Written exam consisting of theoretical and practical parts, POT (final project corrected by tutor).
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- Study Materials
The course is taught annually.
Information on the extent and intensity of the course: tutorial 12 hodin.
- Enrolment Statistics (Spring 2022, recent)
- Permalink: https://is.muni.cz/course/econ/spring2022/BKM_STA2