ESF:BPM_STA2 Statistics 2 - Course Information
BPM_STA2 Statistics 2
Faculty of Economics and AdministrationSpring 2017
- Extent and Intensity
- 2/2/0. 5 credit(s). Type of Completion: graded credit.
- Teacher(s)
- doc. Mgr. Maria Králová, Ph.D. (lecturer)
Mgr. Jan Böhm (seminar tutor)
Mgr. Ondřej Černý (seminar tutor)
doc. Mgr. Maria Králová, Ph.D. (seminar tutor)
Mgr. Štěpán Křehlík, Ph.D. (seminar tutor)
Ing. Mgr. Markéta Matulová, Ph.D. (seminar tutor)
Mgr. et Mgr. Alena Novotná (seminar tutor)
Mgr. Petra Ráboňová, Ph.D. (seminar tutor)
Ing. Mgr. Vlastimil Reichel, Ph.D. (seminar tutor)
Mgr. Tomáš Zdražil (seminar tutor) - 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
- Tue 18:00–19:35 P101
- Timetable of Seminar Groups:
BPM_STA2/T02: Mon 13. 2. to Mon 22. 5. Mon 14:30–16:05 117, Thu 16. 2. to Mon 22. 5. Thu 14:45–16:20 106, A. Novotná, Nepřihlašuje se. Určeno pro studenty se zdravotním postižením.
BPM_STA2/01: Mon 18:00–19:35 VT204, V. Reichel
BPM_STA2/03: Wed 9:20–11:00 VT204, P. Ráboňová
BPM_STA2/04: Thu 11:05–12:45 VT203, P. Ráboňová
BPM_STA2/05: Thu 12:50–14:30 VT203, P. Ráboňová
BPM_STA2/07: Mon 14:35–16:15 VT204, M. Králová
BPM_STA2/08: Thu 9:20–11:00 VT203, T. Zdražil
BPM_STA2/11: Thu 16:20–17:55 VT203, O. Černý
BPM_STA2/14: Thu 12:50–14:30 VT105, Š. Křehlík
BPM_STA2/18: Thu 14:35–16:15 VT204, P. Ráboňová
BPM_STA2/20: Wed 11:05–12:45 VT105, P. Ráboňová - Prerequisites
- ( 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
- Economic Information Systems (programme ESF, B-SI)
- Economics (programme ESF, M-EKT)
- Finance (programme ESF, B-FU)
- Finance (programme ESF, M-FU)
- Economic Policy (programme ESF, B-HPS)
- Economic Policy (programme ESF, M-HPS)
- Business Management (programme ESF, B-EKM)
- Business Management (programme ESF, M-EKM)
- Business Informatics (programme ESF, B-SI)
- Regional Development and Tourism (programme ESF, B-HPS)
- 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.)
- Regional Development and Administration (programme ESF, M-HPS)
- Public Economics and Administration (programme ESF, B-HPS)
- Public Economics and Administration (programme ESF, M-HPS)
- Course objectives
- At the end of the course students should be able to:
- understand and explain the basics of statistical inference;
- use the basic testing procedures;
- operate the statistical software. - Syllabus
- - Normal as well as derived exact distributions (Pearson distribution, Student distribution, F distribution) and their properties; quantile tables.
- - Law of large numbers, central limit theorem.
- - Basic concepts of mathematical statistics; inductive statistics, random sampling, sample statistic.
- - Point estimation and interval estimation of population parameters and parametric functions.
- - Introduction to hypotheses testing.
- - The statistical inferences based on a single sample from normal distribution.
- - The statistical inferences based on two independent samples from the normal distribution.
- - The statistical inferences based on one sample or two independent samples from Bernoulli (zero-one) distribution.
- - One-way analysis of variance.
- - Simple linear regression.
- - Introduction to correlation analysis.
- - The relationship between two variables on the nominal or ordinal scale
- - Nonparametric tests on medians
- Literature
- NOVÁK, Ilja, Richard HINDLS and Stanislava HRONOVÁ. Metody statistické analýzy pro ekonomy. 2. přepracované vyd. Praha: Management Press, 2000, 259 s. ISBN 80-7261-013-9. info
- OSECKÝ, Pavel. Statistické vzorce a věty (Statistical formulas). Druhé rozšířené. Brno (Czech Republic): Masarykova univerzita, Ekonomicko-správní fakulta, 1999, 53 pp. ISBN 80-210-2057-1. info
- BUDÍKOVÁ, Marie, Štěpán MIKOLÁŠ and Pavel OSECKÝ. Popisná statistika (Descriptive Statistics). 3., doplněné vyd. Brno: Masarykova univerzita, 1998, 52 pp. ISBN 80-210-1831-3. info
- BUDÍKOVÁ, Marie, Štěpán MIKOLÁŠ and Pavel OSECKÝ. Teorie pravděpodobnosti a matematická statistika : sbírka příkladů. 2. vyd. Brno: Masarykova univerzita v Brně, 1998, viii, 116. ISBN 8021018321. info
- Teaching methods
- Theoretical lectures; computer seminar sessions.
- Assessment methods
- The final grade is given by the score of the final test.
The requirements for taking the test are:
to be active at seminar sessions which are compulsory and to pass 2 Ropots.
Any copying, recording or leaking tests, use of unauthorized tools, aids and communication devices, or other disruptions of objectivity of exams (credit tests) will be considered non-compliance with the conditions for course completion as well as a severe violation of the study rules. Consequently, the teacher will finish the exam (credit test) by awarding grade "F" in the Information System, and the Dean will initiate disciplinary proceedings that may result in study termination. - Language of instruction
- Czech
- Follow-Up Courses
- Further comments (probably available only in Czech)
- Study Materials
The course is taught annually.
General note: Přednášky jsou dostupné online a ze záznamu.
Information on course enrolment limitations: max. 30 cizích studentů; cvičení pouze pro studenty ESF - Listed among pre-requisites of other courses
- Enrolment Statistics (Spring 2017, recent)
- Permalink: https://is.muni.cz/course/econ/spring2017/BPM_STA2