BPM_STA2 Statistics 2

Faculty of Economics and Administration
Spring 2013
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. Ondřej Černý (seminar tutor)
Mgr. David Hampel, Ph.D. (seminar tutor)
doc. Mgr. Maria Králová, Ph.D. (seminar tutor)
Ing. Mgr. Markéta Matulová, Ph.D. (seminar tutor)
Mgr. Lenka Zavadilová, Ph.D. (seminar tutor)
Mgr. Tomáš Zdražil (seminar tutor)
Guaranteed by
RNDr. Luboš Bauer, CSc.
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
Mon 11:05–12:45 P101
  • Timetable of Seminar Groups:
BPM_STA2/01: Mon 18:00–19:35 VT203, M. Králová
BPM_STA2/02: Tue 12:50–14:30 VT105
BPM_STA2/03: Tue 14:35–16:15 VT105
BPM_STA2/04: Thu 11:05–12:45 VT204, T. Zdražil
BPM_STA2/05: Thu 12:50–14:30 VT203, L. Zavadilová
BPM_STA2/06: Thu 14:35–16:15 VT203, L. Zavadilová
BPM_STA2/07: Thu 7:40–9:15 VT204, T. Zdražil
BPM_STA2/08: Thu 9:20–11:00 VT204, T. Zdražil
BPM_STA2/09: Wed 7:40–9:15 VT105, M. Matulová
BPM_STA2/10: Fri 7:40–9:15 VT204
BPM_STA2/11: Tue 16:20–17:55 VT105, S. Abaffy
BPM_STA2/12: Tue 18:00–19:35 VT105, S. Abaffy
BPM_STA2/13: Mon 7:40–9:15 VT105
BPM_STA2/14: Thu 12:50–14:30 VT105, M. Matulová
BPM_STA2/15: Tue 16:20–17:55 VT204, O. Černý
BPM_STA2/16: Mon 9:20–11:00 VT105
BPM_STA2/17: Tue 18:00–19:35 VT204, O. Černý
BPM_STA2/18: Thu 15:30–17:05 VT204
BPM_STA2/19: Wed 9:20–11:00 VT105, M. Matulová
BPM_STA2/20: Wed 11:05–12:45 VT105, L. Zavadilová
BPM_STA2/21: Wed 12:50–14:30 VT105, L. Zavadilová
BPM_STA2/22: Tue 7:40–9:15 VT203, S. Abaffy
BPM_STA2/23: Thu 7:40–9:15 VT105
BPM_STA2/24: Fri 12:50–14:30 VT203, M. Králová
BPM_STA2/25: Fri 14:35–16:15 VT203, M. Králová
BPM_STA2/26: Thu 14:35–16:15 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
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 set computer-aided solution of the semester paper and to be active at seminar sessions which are compulsory.
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: 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
The course is also listed under the following terms Spring 2010, Spring 2011, Spring 2012, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.
  • Enrolment Statistics (Spring 2013, recent)
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