ESF:BPM_STA2 Statistics 2 - Course Information
BPM_STA2 Statistics 2
Faculty of Economics and AdministrationSpring 2011
- Extent and Intensity
- 2/2/0. 5 credit(s). Type of Completion: graded credit.
- Teacher(s)
- doc. Mgr. Maria Králová, Ph.D. (lecturer)
Mgr. Stanislav Abaffy (seminar tutor)
Mgr. David Hampel, Ph.D. (seminar tutor)
doc. Mgr. Maria Králová, Ph.D. (seminar tutor)
Mgr. Tomáš Lerch (seminar tutor)
Ing. Mgr. Markéta Matulová, Ph.D. (seminar tutor)
Mgr. Jan Orava (seminar tutor) - Guaranteed by
- RNDr. Luboš Bauer, CSc.
Department of Applied Mathematics and Computer Science – Faculty of Economics and Administration
Contact Person: Lenka Hráčková - Timetable
- Mon 11:05–12:45 P101
- Timetable of Seminar Groups:
BPM_STA2/02: Tue 12:50–14:30 VT105, M. Králová
BPM_STA2/03: Tue 14:35–16:15 VT105
BPM_STA2/04: Thu 11:05–12:45 VT206, M. Králová
BPM_STA2/05: Thu 12:50–14:30 VT203, M. Matulová
BPM_STA2/06: Thu 14:35–16:15 VT203, M. Matulová
BPM_STA2/07: Thu 7:40–9:15 VT206, D. Hampel
BPM_STA2/08: Thu 9:20–11:00 VT206
BPM_STA2/09: Wed 7:40–9:15 VT105, S. Abaffy
BPM_STA2/10: Tue 9:20–11:00 VT105, J. Orava
BPM_STA2/11: Tue 16:20–17:55 VT105, J. Orava
BPM_STA2/12: Tue 18:00–19:35 VT105, J. Orava
BPM_STA2/13: Mon 7:40–9:15 VT105, M. Králová
BPM_STA2/14: Thu 12:50–14:30 VT105, M. Králová
BPM_STA2/15: Tue 16:20–17:55 VT206, S. Abaffy
BPM_STA2/16: Mon 9:20–11:00 VT105, M. Králová
BPM_STA2/17: Tue 18:00–19:35 VT206, S. Abaffy
BPM_STA2/18: Thu 15:30–17:05 VT206
BPM_STA2/19: Wed 9:20–11:00 VT105, T. Lerch
BPM_STA2/20: Wed 11:05–12:45 VT105, T. Lerch
BPM_STA2/21: Wed 12:50–14:30 VT105, T. Lerch
BPM_STA2/22: Tue 7:40–9:15 VT203
BPM_STA2/23: Thu 7:40–9:15 VT105 - Prerequisites
- ( STAI Statistics I || Ex_7289_P Statistics I || PMSTAI Statistics I || BPM_STA1 Statistics 1 || PMZM3 Introduction to mathematicsIII ) && (! PMSTII Statistics II )
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)
- Financial Management (programme ESF, M-HPS)
- Economic Policy (programme ESF, M-HPS)
- National Economy (programme ESF, B-HPS)
- Business Management (programme ESF, B-EKM)
- Business Management (programme ESF, M-EKM)
- 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 (programme ESF, B-HPS)
- Public Economics (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
- recommended 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
- not specified
- 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
- 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
- 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 set computer-aided solution of the semester paper and to be active at seminar sessions which are compulsory. - Language of instruction
- Czech
- Follow-Up Courses
- Further comments (probably available only in Czech)
- The course is taught annually.
General note: Nezapisují si studenti, kteří absolvovali předmět PMSTII.
Information on course enrolment limitations: max. 30 cizích studentů; cvičení pouze pro studenty ESF - Listed among pre-requisites of other courses
- Enrolment Statistics (Spring 2011, recent)
- Permalink: https://is.muni.cz/course/econ/spring2011/BPM_STA2