ESF:BPM_STA2 Statistics 2 - Course Information

BPM_STA2 Statistics 2

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)
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)
Mgr. Tomáš Zdražil (seminar tutor)
Mgr. Silvie Zlatošová, Ph.D. (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, T. Lerch
BPM_STA2/03: Tue 14:35–16:15 VT105, T. Lerch
BPM_STA2/04: Thu 11:05–12:45 VT206, J. Orava
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, M. Matulová
BPM_STA2/08: Thu 9:20–11:00 VT206, J. Orava
BPM_STA2/09: Wed 7:40–9:15 VT105
BPM_STA2/10: Mon 12:50–14:30 VT206, M. Králová
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, J. Orava
BPM_STA2/15: Tue 16:20–17:55 VT206, T. Lerch
BPM_STA2/16: Mon 9:20–11:00 VT105
BPM_STA2/17: Tue 18:00–19:35 VT206
BPM_STA2/18: Thu 15:30–17:05 VT206
BPM_STA2/19: Wed 9:20–11:00 VT105, S. Zlatošová
BPM_STA2/20: Wed 11:05–12:45 VT105, S. Zlatošová
BPM_STA2/21: Wed 12:50–14:30 VT105, S. Zlatošová
BPM_STA2/22: Tue 7:40–9:15 VT203, S. Abaffy
BPM_STA2/23: Thu 7:40–9:15 VT105, T. Zdražil
BPM_STA2/24: Fri 12:50–14:30 VT203, M. Králová
BPM_STA2/25: Fri 14:35–16:15 VT203, M. Králová

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

there are 21 fields of study the course is directly associated with, display

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.

Language of instruction

Czech

Follow-Up Courses

• BPE_CARA Time Series

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

• BPM_STAE Statistics for economists
  (!BPM_STA1)||(!BPM_STA2)  

• Enrolment Statistics (Spring 2012, recent)
  
• Permalink: https://is.muni.cz/course/econ/spring2012/BPM_STA2