MPH_ASDM Analysis of statistical data for managers

Faculty of Economics and Administration
Autumn 2022
Extent and Intensity
0/2/0. 3 credit(s). Type of Completion: zk (examination).
Teacher(s)
doc. Ing. Ondřej Částek, Ph.D. (seminar tutor)
Ing. Peter Mikuš (seminar tutor)
Guaranteed by
doc. Ing. Ondřej Částek, Ph.D.
Department of Business Management – Faculty of Economics and Administration
Contact Person: Vlasta Radová
Supplier department: Department of Business Management – Faculty of Economics and Administration
Timetable of Seminar Groups
MPH_ASDM/01: Thu 12:00–13:50 VT206, except Thu 15. 9., except Thu 3. 11., O. Částek, P. Mikuš
Prerequisites
The pre-requisite is knowledge of basic statistics. This course therefore deepens this knowledge and adds specifics of data typically used by managers.
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.

The capacity limit for the course is 50 student(s).
Current registration and enrolment status: enrolled: 2/50, only registered: 0/50
fields of study / plans the course is directly associated with
Course objectives
The objective is to build competency of independent application of chosen methods of statistical analysis on data typical for the management field. This course is intended for students of Business Management master degree and assumes knowledge of basic statistical analyses from the bachelor degree. These analyses are not discussed on the theoretical level, but are applied on real data. The tool of acquiring the above-mentioned competency is work with real data in SPSS program, where our work will start with a research question, operationalized into hypotheses. Data will be processed using univariate analyses and afterwards the hypotheses will be tested using bivariate and multivariate analyses. Using real data should support, among others the transfer to a knowledge society.
Learning outcomes
Student will be, after successfully finishing the course, capable of:
1. independent data analyses,
2. formulating research questions and their operationalization into hypotheses,
3. cleaning the data and understanding them through the cleaning and descriptive statistics,
4. testing hypotheses, especially using the bivariate and multivariate statistics,
5. interpreting the obtained results, creating new knowledge.
Syllabus
  • Course contents:
  • 1. Hypotheses and models
  • 2. Types of variables
  • 3. Univariate analysis
  • 4. Inference and hypothesis testing
  • 5. T-test, ANOVA
  • 6. Chi-square
  • 7. Correlations, associations
  • 8. Elaboration - examining mediators/moderators
  • 9. Linear regression
  • 10. Multiple linear regression
Literature
    required literature
  • FIELD, Andy P. Discovering statistics using IBM SPSS statistics. 5th edition. Los Angeles: Sage, 2018, xxix, 1070. ISBN 9781526419521. info
  • MAREŠ, Petr, Ladislav RABUŠIC and Petr SOUKUP. Analýza sociálněvědních dat (nejen) v SPSS (Data analysis in social sciences (using SPSS)). První. Brno: Masarykova univerzita, 2015, 508 pp. ISBN 978-80-210-6362-4. info
  • DISMAN, Miroslav. Jak se vyrábí sociologická znalost : příručka pro uživatele. 4. nezměněné vydání. Praha: Univerzita Karlova v Praze, nakladatelství Karolinum, 2011, 372 stran. ISBN 9788024619668. URL info
  • HENDL, Jan. Přehled statistických metod : analýza a metaanalýza dat. Páté, rozšířené vydán. Praha: Portál, 2015, 734 stran. ISBN 9788026209812. info
    recommended literature
  • SOUKUP, Petr and Ladislav RABUŠIC. Několik poznámek k jedné obsesi českých sociálních věd, statistické významnosti (Some Notes on the Obsession of the Czech Social Sciences with Statistical Significance). Sociologický časopis/ Czech Sociological Review. Praha: Sociologický ústav AV ČR, 2007, vol. 43, No 2, p. 379-395. ISSN 0038-0288. info
Teaching methods
Seminars, solving tasks on PC in seminars and outside the seminars.
Assessment methods
Students will be given tasks to be solved during the semester. They can obtain up to 50 points for their successful solution. Another 50 points will be available at a final exam on PC. The grading system is:
• 100 - 93% = A
• 92.9 - 85% = B
• 84.9 - 77% = C
• 76.9 - 69% = D
• 68.9 - 60% = E
• 59.9 - 0% = F
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
Information on course enrolment limitations: Minimální počet pro otevření předmětu je 10 zapsaných studentů. / The minimum number of enrolled students to open the course is 10.
The course is also listed under the following terms Autumn 2020, Autumn 2021.
  • Enrolment Statistics (recent)
  • Permalink: https://is.muni.cz/course/econ/autumn2022/MPH_ASDM