Course Information

BPM_STA2 Statistics 2

Extent and Intensity

2/2/0. 5 credit(s). Type of Completion: zk (examination).

Teacher(s)

Mgr. Petra Ráboňová, Ph.D. (lecturer)
Ing. Matouš Cabalka (seminar tutor)
Mgr. Bc. Martin Chvátal, Ph.D. (seminar tutor)
Ing. Mgr. Markéta Matulová, Ph.D. (seminar tutor)
Mgr. Petra Ráboňová, Ph.D. (seminar tutor)
Ing. Mgr. Vlastimil Reichel, Ph.D. (seminar tutor)

Guaranteed by

Mgr. Petra Ráboňová, Ph.D.
Division of Applied Mathematics and Computer Science – Faculty of Economics and Administration
Contact Person: Lenka Hráčková
Supplier department: Division of Applied Mathematics and Computer Science – Faculty of Economics and Administration

Timetable

Tue 12:00–13:50 P101, except Tue 2. 4.

• Timetable of Seminar Groups:

BPM_STA2/02: Wed 8:00–9:50 VT204, except Wed 3. 4., P. Ráboňová
BPM_STA2/03: Thu 10:00–11:50 VT314, except Thu 4. 4., M. Matulová
BPM_STA2/05: Thu 8:00–9:50 VT314, except Thu 4. 4., P. Ráboňová
BPM_STA2/07: Thu 12:00–13:50 VT105, except Thu 4. 4., M. Chvátal
BPM_STA2/09: Wed 10:00–11:50 VT314, except Wed 3. 4., P. Ráboňová
BPM_STA2/10: Wed 12:00–13:50 VT202, except Wed 3. 4., M. Cabalka
BPM_STA2/11: Wed 14:00–15:50 VT202, except Wed 3. 4., V. Reichel
BPM_STA2/12: Tue 14:00–15:50 VT314, except Tue 2. 4., P. Ráboňová
BPM_STA2/14: Wed 10:00–11:50 VT206, except Wed 3. 4., M. Matulová
BPM_STA2/15: Thu 10:00–11:50 VT202, except Thu 4. 4., M. Cabalka
BPM_STA2/16: Wed 8:00–9:50 VT314, except Wed 3. 4., M. Cabalka
BPM_STA2/17: Thu 8:00–9:50 VT202, except Thu 4. 4., M. Cabalka
BPM_STA2/18: Wed 10:00–11:50 VT105, except Wed 3. 4., M. Cabalka
BPM_STA2/19: Mon 18:00–19:50 VT314, except Mon 1. 4., M. Cabalka
BPM_STA2/20: Thu 10:00–11:50 VT206, except Thu 4. 4., 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

there are 13 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.

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

• - Normal as well as derived exact distributions (Pearson distribution, Student distribution, F distribution) and their properties; quantile tables.
• - 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

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
• MANN, Prem S. Mann's introductory statistics. Global edition. Hoboken: Wiley, 2016, xiv, 544. ISBN 9781119248941. info

Teaching methods

Theoretical lectures; computer seminar sessions.

Assessment methods

Lecture with a seminar
Test requirements:
1. Adequately active participation at seminars
2. Success at ROPOT tests
3. Success at final test
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

• BPE_CARA Time Series

Further comments (probably available only in Czech)

Study Materials
The course is taught annually.
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)  

BPM_STA2 Statistics 2

Extent and Intensity

2/2/0. 5 credit(s). Type of Completion: zk (examination).

Teacher(s)

Mgr. Petra Ráboňová, Ph.D. (lecturer)
Ing. Matouš Cabalka (seminar tutor)
Mgr. Martin Dzúrik (seminar tutor)
Mgr. Bc. Martin Chvátal, Ph.D. (seminar tutor)
Ing. Lukáš Kokrda (seminar tutor)
Ing. Mgr. Markéta Matulová, Ph.D. (seminar tutor)
Mgr. Petra Ráboňová, Ph.D. (seminar tutor)
Ing. Mgr. Vlastimil Reichel, Ph.D. (seminar tutor)

Guaranteed by

Mgr. Petra Ráboňová, 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 12:00–13:50 P101, except Tue 28. 3.

• Timetable of Seminar Groups:

BPM_STA2/01: Tue 16:00–17:50 VT314, except Tue 28. 3.
BPM_STA2/02: Wed 8:00–9:50 VT204, except Wed 29. 3., M. Cabalka
BPM_STA2/03: Thu 10:00–11:50 VT206, except Thu 30. 3., M. Chvátal
BPM_STA2/05: Thu 8:00–9:50 VT314, except Thu 30. 3., M. Chvátal
BPM_STA2/08: Thu 12:00–13:50 VT204, except Thu 30. 3., M. Matulová
BPM_STA2/09: Tue 16:00–17:50 VT204, except Tue 28. 3., P. Ráboňová
BPM_STA2/10: Wed 10:00–11:50 VT204, except Wed 29. 3., M. Cabalka
BPM_STA2/11: Wed 12:00–13:50 VT202, except Wed 29. 3., V. Reichel
BPM_STA2/12: Wed 14:00–15:50 VT202, except Wed 29. 3., V. Reichel
BPM_STA2/13: Tue 14:00–15:50 VT314, except Tue 28. 3., P. Ráboňová
BPM_STA2/14: Thu 18:00–19:50 VT202, except Thu 30. 3., M. Dzúrik
BPM_STA2/15: Thu 14:00–15:50 VT314, except Thu 30. 3., M. Chvátal
BPM_STA2/16: Thu 16:00–17:50 VT314, except Thu 30. 3., M. Dzúrik

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

there are 13 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.

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

• - 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

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

not specified
• WEISS, N. A. Introductory statistics. Edited by Carol A. Weiss. 10th edition, global edition. Boston: Pearson, 2017, 763, 73. ISBN 9781292099729. 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

• BPE_CARA Time Series

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

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

BPM_STA2 Statistics 2

Extent and Intensity

2/2/0. 5 credit(s). Type of Completion: zk (examination).

Teacher(s)

doc. Mgr. Maria Králová, Ph.D. (lecturer)
Mgr. Jan Böhm (seminar tutor)
Ing. Matouš Cabalka (seminar tutor)
Mgr. Bc. Martin Chvátal, Ph.D. (seminar tutor)
Ing. Lukáš Kokrda (seminar tutor)
doc. Mgr. Maria Králová, Ph.D. (seminar tutor)
Ing. Mgr. Markéta Matulová, Ph.D. (seminar tutor)
Mgr. Petra Ráboňová, Ph.D. (seminar tutor)
Ing. Mgr. Vlastimil Reichel, Ph.D. (seminar tutor)
Ing. Jana Vechetová (seminar tutor)
Mgr. Lenka Zavadilová, Ph.D. (seminar tutor)
Mgr. et Mgr. Iva Raclavská, DiS. (assistant)

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 12:00–13:50 P101, except Tue 29. 3.

• Timetable of Seminar Groups:

BPM_STA2/01: Tue 16:00–17:50 VT105, except Tue 29. 3., M. Cabalka
BPM_STA2/02: Wed 8:00–9:50 VT204, except Wed 30. 3., M. Chvátal
BPM_STA2/03: Thu 10:00–11:50 VT206, except Thu 31. 3., P. Ráboňová
BPM_STA2/04: Thu 12:00–13:50 VT206, except Thu 31. 3., P. Ráboňová
BPM_STA2/05: Thu 8:00–9:50 VT105, except Thu 31. 3., M. Matulová
BPM_STA2/06: Tue 12:00–13:50 VT206, except Tue 29. 3.
BPM_STA2/07: Thu 8:00–9:50 VT206, except Thu 31. 3., P. Ráboňová
BPM_STA2/08: Tue 18:00–19:50 VT206, except Tue 29. 3., J. Vechetová
BPM_STA2/09: Thu 12:00–13:50 VT204, except Thu 31. 3., M. Matulová
BPM_STA2/10: Thu 14:00–15:50 VT204, except Thu 31. 3.
BPM_STA2/11: Wed 10:00–11:50 VT202, except Wed 30. 3.
BPM_STA2/12: Tue 16:00–17:50 VT204, except Tue 29. 3., J. Vechetová
BPM_STA2/13: Thu 10:00–11:50 VT105, except Thu 31. 3.
BPM_STA2/14: Thu 16:00–17:50 VT206, except Thu 31. 3.
BPM_STA2/15: Wed 8:00–9:50 VT105, except Wed 30. 3.
BPM_STA2/16: Wed 10:00–11:50 VT204, except Wed 30. 3., M. Chvátal
BPM_STA2/17: Wed 12:00–13:50 VT202, except Wed 30. 3., V. Reichel
BPM_STA2/18: Wed 14:00–15:50 VT202, except Wed 30. 3., V. Reichel
BPM_STA2/19: Tue 14:00–15:50 VT105, except Tue 29. 3., M. Cabalka
BPM_STA2/20: Tue 18:00–19:50 VT105, except Tue 29. 3.
BPM_STA2/21: Thu 18:00–19:50 VT202, except Thu 31. 3.
BPM_STA2/22: Tue 16:00–17:50 VT202, except Tue 29. 3.

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

there are 22 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.

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

• - 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

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

not specified
• WEISS, N. A. Introductory statistics. Edited by Carol A. Weiss. 10th edition, global edition. Boston: Pearson, 2017, 763, 73. ISBN 9781292099729. 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

• BPE_CARA Time Series

Further comments (probably available only in Czech)

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

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

BPM_STA2 Statistics 2

Extent and Intensity

2/2/0. 5 credit(s). Type of Completion: zk (examination).

Teacher(s)

doc. Mgr. Maria Králová, Ph.D. (lecturer)
Mgr. Jan Böhm (seminar tutor)
Ing. Matouš Cabalka (seminar tutor)
Mgr. Terézia Černá (seminar tutor)
Lenka Hráčková (seminar tutor)
Mgr. Bc. Martin Chvátal, Ph.D. (seminar tutor)
doc. Mgr. Maria Králová, Ph.D. (seminar tutor)
Ing. Mgr. Markéta Matulová, Ph.D. (seminar tutor)
Mgr. Petra Ráboňová, Ph.D. (seminar tutor)
Ing. Mgr. Vlastimil Reichel, Ph.D. (seminar tutor)
Ing. Jana Vechetová (seminar tutor)
Mgr. Lenka Zavadilová, Ph.D. (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 12:00–13:50 P101

• Timetable of Seminar Groups:

BPM_STA2/01: Tue 16:00–17:50 VT202
BPM_STA2/02: Wed 8:00–9:50 VT204, T. Černá
BPM_STA2/03: Thu 10:00–11:50 VT206, J. Böhm
BPM_STA2/04: Thu 12:00–13:50 VT206, M. Matulová
BPM_STA2/05: Thu 8:00–9:50 VT105, T. Černá
BPM_STA2/06: Tue 14:00–15:50 VT204, J. Böhm
BPM_STA2/07: Thu 8:00–9:50 VT206, M. Matulová
BPM_STA2/08: Tue 18:00–19:50 VT206, J. Böhm
BPM_STA2/09: Thu 12:00–13:50 VT204, M. Chvátal
BPM_STA2/10: Thu 14:00–15:50 VT204, M. Chvátal
BPM_STA2/11: Wed 10:00–11:50 VT202
BPM_STA2/12: Tue 16:00–17:50 VT204, J. Böhm
BPM_STA2/13: Thu 10:00–11:50 VT105, T. Černá
BPM_STA2/14: Thu 16:00–17:50 VT206, M. Chvátal
BPM_STA2/15: Wed 8:00–9:50 VT105, M. Chvátal
BPM_STA2/16: Wed 10:00–11:50 VT204, T. Černá
BPM_STA2/17: Wed 12:00–13:50 VT202, V. Reichel
BPM_STA2/18: Wed 14:00–15:50 VT202, V. Reichel
BPM_STA2/19: Tue 14:00–15:50 VT105
BPM_STA2/20: Tue 18:00–19:50 VT105

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

there are 22 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.

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

• - 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

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

not specified
• WEISS, N. A. Introductory statistics. Edited by Carol A. Weiss. 10th edition, global edition. Boston: Pearson, 2017, 763, 73. ISBN 9781292099729. 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

• BPE_CARA Time Series

Further comments (probably available only in Czech)

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

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

BPM_STA2 Statistics 2

Extent and Intensity

2/2/0. 5 credit(s). Type of Completion: zk (examination).

Teacher(s)

doc. Mgr. Maria Králová, Ph.D. (lecturer)
Mgr. Jan Böhm (seminar tutor)
Ing. Matouš Cabalka (seminar tutor)
Mgr. Terézia Černá (seminar tutor)
Mgr. Monika Filová (seminar tutor)
Mgr. Bc. Martin Chvátal, Ph.D. (seminar tutor)
Ing. Lukáš Kokrda (seminar tutor)
doc. Mgr. Maria Králová, Ph.D. (seminar tutor)
Ing. Mgr. Markéta Matulová, Ph.D. (seminar tutor)
Mgr. Petra Ráboňová, Ph.D. (seminar tutor)
Ing. Mgr. Vlastimil Reichel, Ph.D. (seminar tutor)
Lenka Hráčková (assistant)

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 12:00–13:50 P101

• Timetable of Seminar Groups:

BPM_STA2/T01: Mon 17. 2. to Sun 24. 5. Mon 10:00–11:50 Knihovna ESF, box 2, V. Reichel, Nepřihlašuje se. Určeno pro studenty se zdravotním postižením.
BPM_STA2/01: Tue 16:00–17:50 VT202, T. Černá
BPM_STA2/02: Wed 8:00–9:50 VT204, J. Böhm
BPM_STA2/03: Thu 10:00–11:50 VT206, L. Kokrda
BPM_STA2/04: Thu 12:00–13:50 VT206, M. Matulová
BPM_STA2/05: Thu 8:00–9:50 VT105, P. Ráboňová
BPM_STA2/06: Tue 14:00–15:50 VT204, M. Filová, M. Králová
BPM_STA2/07: Thu 8:00–9:50 VT206
BPM_STA2/08: Tue 18:00–19:50 VT206, T. Černá
BPM_STA2/09: Thu 12:00–13:50 VT204, P. Ráboňová
BPM_STA2/10: Thu 14:00–15:50 VT204, P. Ráboňová
BPM_STA2/11: Wed 10:00–11:50 VT202, J. Böhm
BPM_STA2/13: Tue 16:00–17:50 VT204, M. Filová
BPM_STA2/14: Thu 10:00–11:50 VT105, P. Ráboňová
BPM_STA2/16: Thu 16:00–17:50 VT206, M. Cabalka

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

there are 22 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.

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

• - 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

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, 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
• 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

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

• BPE_CARA Time Series

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

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

BPM_STA2 Statistics 2

Extent and Intensity

2/2/0. 5 credit(s). Type of Completion: zk (examination).

Teacher(s)

doc. Mgr. Maria Králová, Ph.D. (lecturer)
Mgr. Jan Böhm (seminar tutor)
Mgr. Terézia Černá (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)

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 12:00–13:50 P101

• Timetable of Seminar Groups:

BPM_STA2/01: Mon 18:00–19:50 VT204, V. Reichel
BPM_STA2/02: Wed 8:00–9:50 VT204, J. Böhm
BPM_STA2/03: Thu 10:00–11:50 VT206, J. Böhm
BPM_STA2/04: Thu 12:00–13:50 VT206, P. Ráboňová
BPM_STA2/05: Tue 16:00–17:50 VT206, P. Ráboňová
BPM_STA2/06: Tue 14:00–15:50 VT204, M. Králová
BPM_STA2/07: Thu 8:00–9:50 VT206, J. Böhm
BPM_STA2/08: Tue 18:00–19:50 VT206, P. Ráboňová
BPM_STA2/09: Thu 12:00–13:50 VT202, M. Matulová
BPM_STA2/10: Thu 14:00–15:50 VT204, P. Ráboňová
BPM_STA2/11: Wed 10:00–11:50 VT202, J. Böhm
BPM_STA2/12: Wed 14:00–15:50 VT202, Š. Křehlík
BPM_STA2/13: Tue 16:00–17:50 VT202, T. Černá

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

there are 16 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

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, 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
• 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

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

• BPE_CARA Time Series

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

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

BPM_STA2 Statistics 2

Extent and Intensity

2/2/0. 5 credit(s). Type of Completion: zk (examination).

Teacher(s)

doc. Mgr. Maria Králová, Ph.D. (lecturer)
Mgr. Jan Böhm (seminar tutor)
Mgr. Ondřej Černý (seminar tutor)
Ing. Pavel Chlup (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 12:50–14:30 P101

• Timetable of Seminar Groups:

BPM_STA2/01: Mon 18:00–19:35 VT204, V. Reichel
BPM_STA2/03: Wed 9:20–11:00 VT204, J. Böhm
BPM_STA2/04: Thu 11:05–12:45 VT206, Š. Křehlík
BPM_STA2/05: Thu 12:50–14:30 VT206, J. Böhm
BPM_STA2/06: Tue 16:20–17:55 VT206, O. Černý
BPM_STA2/07: Tue 14:35–16:15 VT204, M. Králová
BPM_STA2/08: Thu 9:20–11:00 VT206, P. Chlup
BPM_STA2/09: Tue 18:00–19:35 VT206, O. Černý
BPM_STA2/14: Thu 12:50–14:30 VT105, M. Matulová
BPM_STA2/18: Thu 14:35–16:15 VT204, J. Böhm
BPM_STA2/20: Wed 11:05–12:45 VT105, J. Böhm

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

there are 16 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

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, 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
• 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

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

• BPE_CARA Time Series

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

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

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. 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/T01: Wed 22. 2. to Mon 22. 5. each even Wednesday 8:00–11:15 118, V. Reichel, Nepřihlašuje se. Určeno pro studenty se zdravotním postižením.
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

there are 16 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 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

• BPE_CARA Time Series

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

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

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. Ondřej Černý (seminar tutor)
doc. Mgr. Maria Králová, 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/T01: Mon 29. 2. to Fri 20. 5. Mon 8:45–10:25 118, V. Reichel
BPM_STA2/04: Thu 11:05–12:45 VT203, P. Ráboňová
BPM_STA2/05: Thu 12:50–14:30 VT203, P. Ráboňová
BPM_STA2/06: Thu 14:35–16:15 VT203, M. Matulová
BPM_STA2/07: Mon 14:35–16:15 VT204, M. Králová
BPM_STA2/08: Thu 9:20–11:00 VT203, T. Zdražil
BPM_STA2/10: Fri 7:40–9:15 VT105, P. Ráboňová
BPM_STA2/11: Thu 16:20–17:55 VT203, O. Černý
BPM_STA2/12: Thu 18:00–19:35 VT203, O. Černý
BPM_STA2/14: Thu 12:50–14:30 VT105, M. Matulová
BPM_STA2/18: Thu 14:35–16:15 VT204, P. Ráboňová
BPM_STA2/19: Wed 9:20–11:00 VT105, V. Reichel
BPM_STA2/20: Wed 11:05–12:45 VT105, V. Reichel
BPM_STA2/21: Wed 12:50–14:30 VT105, M. Matulová
BPM_STA2/23: Thu 7:40–9:15 VT105, T. Zdražil

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

there are 16 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 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

• BPE_CARA Time Series

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

Information about innovation of course.

This course has been innovated under the project "Inovace studia ekonomických disciplín v souladu s požadavky znalostní ekonomiky (CZ.1.07/2.2.00/28.0227)" which is cofinanced by the European Social Fond and the national budget of the Czech Republic.

Listed among pre-requisites of other courses

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

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. Ondřej Černý (seminar tutor)
doc. Mgr. Maria Králová, Ph.D. (seminar tutor)
Ing. Mgr. Markéta Matulová, Ph.D. (seminar tutor)
Mgr. Petra Ráboňová, Ph.D. (seminar tutor)
Mgr. Tomáš Zdražil (seminar tutor)
Ing. Josef Nešleha (assistant)

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 9:20–11:00 P101

• Timetable of Seminar Groups:

BPM_STA2/01: No timetable has been entered into IS., Tato skupina bude otevřena jen v případě naplnění ostatních skupin
BPM_STA2/02: No timetable has been entered into IS., Tato skupina bude otevřena jen v případě naplnění ostatních skupin
BPM_STA2/03: No timetable has been entered into IS., Tato skupina bude otevřena jen v případě naplnění ostatních skupin
BPM_STA2/04: Thu 11:05–12:45 VT203, T. Zdražil
BPM_STA2/05: No timetable has been entered into IS., Tato skupina bude otevřena jen v případě naplnění všech ostatních skupin
BPM_STA2/06: Thu 14:35–16:15 VT203, T. Zdražil
BPM_STA2/07: No timetable has been entered into IS., Tato skupina bude otevřena jen v případě naplnění všech ostatních skupin
BPM_STA2/08: Thu 9:20–11:00 VT203, T. Zdražil
BPM_STA2/09: No timetable has been entered into IS., Tato skupina bude otevřena jen v případě naplnění ostatních skupin
BPM_STA2/10: No timetable has been entered into IS., Tato skupina bude otevřena jen v případě naplnění ostatních skupin
BPM_STA2/11: Tue 16:20–17:55 VT105, P. Ráboňová
BPM_STA2/12: No timetable has been entered into IS. P. Ráboňová, Tato skupina bude otevřena jen v případě naplnění ostatních skupin
BPM_STA2/13: No timetable has been entered into IS., Tato skupina bude otevřena jen v případě naplnění ostatních skupin
BPM_STA2/14: Thu 12:50–14:30 VT105, M. Matulová
BPM_STA2/15: Tue 16:20–17:55 VT204, O. Černý
BPM_STA2/17: Tue 18:00–19:35 VT204, O. Černý
BPM_STA2/18: No timetable has been entered into IS., Tato skupina bude otevřena jen v případě naplnění ostatních skupin
BPM_STA2/19: Wed 9:20–11:00 VT105, M. Matulová
BPM_STA2/20: No timetable has been entered into IS., Tato skupina bude otevřena jen v případě naplnění ostatních skupin
BPM_STA2/21: Wed 12:50–14:30 VT105, M. Matulová
BPM_STA2/22: No timetable has been entered into IS., Tato skupina bude otevřena jen v případě naplnění ostatních skupin
BPM_STA2/23: No timetable has been entered into IS., Tato skupina bude otevřena jen v případě naplnění ostatních skupin
BPM_STA2/24: Fri 11:05–12:45 VT203, P. Ráboňová
BPM_STA2/25: Fri 12:50–14:30 VT203, P. Ráboňová
BPM_STA2/26: Fri 9:20–11:00 VT105, P. Ráboňová
BPM_STA2/27: Mon 16:20–17:55 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 16 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.
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

• BPE_CARA Time Series

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

Information about innovation of course.

This course has been innovated under the project "Inovace studia ekonomických disciplín v souladu s požadavky znalostní ekonomiky (CZ.1.07/2.2.00/28.0227)" which is cofinanced by the European Social Fond and the national budget of the Czech Republic.

Listed among pre-requisites of other courses

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

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)
Mgr. Ondřej Černý (seminar tutor)
doc. Mgr. Maria Králová, Ph.D. (seminar tutor)
Ing. Mgr. Markéta Matulová, 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, Tato skupina bude otevřena jen v případě naplnění ostatních skupin
BPM_STA2/03: Tue 14:35–16:15 VT105, Tato skupina bude otevřena jen v případě naplnění ostatních skupin
BPM_STA2/04: Thu 11:05–12:45 VT203, T. Zdražil
BPM_STA2/05: Thu 12:50–14:30 VT203, Tato skupina bude otevřena jen v případě naplnění všech ostatních skupin
BPM_STA2/06: Thu 14:35–16:15 VT203, Tato skupina bude otevřena jen v případě naplnění všech ostatních skupin
BPM_STA2/07: Thu 7:40–9:15 VT204, Tato skupina bude otevřena jen v případě naplnění všech ostatních skupin
BPM_STA2/08: Thu 9:20–11:00 VT203, Tato skupina bude otevřena jen v případě naplnění všech ostatních skupin
BPM_STA2/09: Wed 7:40–9:15 VT105, M. Matulová
BPM_STA2/10: Fri 7:40–9:15 VT204, Tato skupina bude otevřena jen v případě naplnění ostatních skupin
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, Tato skupina bude otevřena jen v případě naplnění ostatních skupin
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, Tato skupina bude otevřena jen v případě naplnění ostatních skupin
BPM_STA2/17: Tue 18:00–19:35 VT204, O. Černý
BPM_STA2/18: Thu 15:30–17:05 VT204, Tato skupina bude otevřena jen v případě naplnění ostatních skupin
BPM_STA2/19: Wed 9:20–11:00 VT105, M. Matulová
BPM_STA2/20: Wed 11:05–12:45 VT105, S. Abaffy
BPM_STA2/21: Wed 12:50–14:30 VT105, S. Abaffy
BPM_STA2/22: Tue 7:40–9:15 VT203, S. Abaffy
BPM_STA2/23: Thu 7:40–9:15 VT105, Tato skupina bude otevřena jen v případě naplnění ostatních skupin
BPM_STA2/24: Fri 12:00–13:35 VT203, Tato skupina bude otevřena jen v případě naplnění ostatních skupin
BPM_STA2/25: Fri 13:45–15:20 VT203, M. Králová
BPM_STA2/26: Thu 14:35–16:15 VT105, Tato skupina bude otevřena jen v případě naplnění ostatních skupin
BPM_STA2/27: Mon 16:20–17:55 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.
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

• BPE_CARA Time Series

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

Information about innovation of course.

This course has been innovated under the project "Inovace studia ekonomických disciplín v souladu s požadavky znalostní ekonomiky (CZ.1.07/2.2.00/28.0227)" which is cofinanced by the European Social Fond and the national budget of the Czech Republic.

Listed among pre-requisites of other courses

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

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)
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

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.
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

• BPE_CARA Time Series

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

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

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)  

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)
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_STA2/01: Tue 11:05–12:45 VT105, M. Králová
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

there are 15 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

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

• 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)  

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. David Hampel, Ph.D. (seminar tutor)
Mgr. Pavla Krajíčková, 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)

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_STA2/01: Tue 11:05–12:45 VT105, M. Králová
BPM_STA2/02: Tue 12:50–14:30 VT105, M. Králová
BPM_STA2/03: Tue 14:35–16:15 VT105, T. Lerch
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, D. Hampel
BPM_STA2/09: Tue 7:40–9:15 VT105, P. Krajíčková
BPM_STA2/10: Tue 9:20–11:00 VT105, P. Krajíčková
BPM_STA2/11: Tue 16:20–17:55 VT105, T. Lerch
BPM_STA2/12: Tue 18:00–19:35 VT105, T. Lerch
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
BPM_STA2/16: Mon 9:20–11:00 VT105, M. Králová
BPM_STA2/17: Tue 18:00–19:35 VT206
BPM_STA2/18: Thu 15:30–17:05 VT206

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)
• Financial Management (programme ESF, M-HPS)
• Regional Development and Administration (programme ESF, M-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

• 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 (recent)