Course: Statistical Data Analysis

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Course title Statistical Data Analysis
Course code KZU/SADMN
Organizational form of instruction Seminar
Level of course Master
Year of study not specified
Semester Winter and summer
Number of ECTS credits 3
Language of instruction Czech
Status of course unspecified
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Peterová Věra, Mgr. Ph.D.
Course content
1. Introduction to the course and completion requirements 2. Introduction to using a computer for data analysis 3. Basics of using STATISTICA or SPSS 4. Univariate analysis 5. Cardinal variables; means for subsets 6. Bivariate analysis - contingency tables and chi-square 7. Variable transformations, case selection 8. Comparison of means and analysis of variance 9. Bivariate analysismeasuring the strength and significance of associations between two variables 10. Correlation analysis 11. Regression analysis 12. Checking for associations with additional factors 13. Applications of statistical data analysis in media research

Learning activities and teaching methods
Monologic Lecture(Interpretation, Training), Dialogic Lecture (Discussion, Dialog, Brainstorming), Activating (Simulations, Games, Dramatization)
  • Preparation for the Course Credit - 20 hours per semester
Learning outcomes
The course introduces students to the basics of working with mass data using SPSS and STATISTICA. Students will learn how to create your own data files and the basics of the data matrix, a data file. It teaches basic skills for analysis of qualitative data with Statistica software (univariate and bivariate analysis, contingent crosstabs, correlation, analysis of regression).
Students will - gain methodological knowledge and insight into mathematical and statistical data anlysis, - work with scholarly text on research methodology, - acquire practical skill and experience in creation of instruments for obtaining of statistical data, - acquire practical skill and experience in data procession, - acquire practical skill and experience in data analysis, - based on own analysis, be able to prepare a research report.
Prerequisites
Basic knowledge of research methodology of social sciences and the basic skill of work on PC.

Assessment methods and criteria
Written exam, Systematic Observation of Student

Elaboration of a tasks of an analysis on a particular data set. Analytical report based on assigned data (written exam).
Recommended literature
  • Adams, K. A., & Lawrence, E. K. Research methods, statistics, and applications.
  • Berger, A. A. Media and communication research methods: an introduction to qualitative and quantitative approaches.
  • Bohrenstedt, G.W., Knoke, D. Statistics for Social Data Analysis. Itasca, Illinois: F.E. Pacock Publishers, Inc..
  • Disman, M. Jak se vyrábí sociologická znalost, Praha, Karolinum 1993, kap. 8.
  • Knapp, H. (2014). Introductory statistics using SPSS. Thousand Oaks, Calif.
  • Loučková, I. 1991. Základní statistické přístupy v sociologickém výzkumu. Olomouc:UP.
  • Meloun, M., Militký, J. 1998. Statistické zpracování experimentálních dat. Praha: Ars magna..
  • Sedláková, R. (2014). Výzkum médií: nejužívanější metody a techniky. Praha.
  • Swoboda, H. Moderní statistika. Praha:Svoboda.
  • Wonnacot T.H., Wonnacot R.J. Statistika pro obchod a hospodářství. Praha: Victoria Publishing.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester