Course: Statistical Analysis of Research Data

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Course title Statistical Analysis of Research Data
Course code KEMCH/C781
Organizational form of instruction Lecture + Seminary
Level of course Master
Year of study not specified
Semester Winter
Number of ECTS credits 5
Language of instruction Czech
Status of course Compulsory
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Paták Michal, doc. Ing. Ph.D.
Course content
Data file preparation - organization of data from questionnaire survey in data matrix. Data file preparation - data transformation and filtering. Exploratory analysis of a one-dimensional file. Inference analysis of one-dimensional file. Statistical hypothesis testing - parametric t-tests, single-factor analysis of variance. Testing of statistical hypotheses - non-parametric tests. Correlation and regression analysis. Categorized data analysis in PivotTable. Multiple linear regression. Factor analysis. Cluster analysis. Time series analysis. Reporting research results.

Learning activities and teaching methods
Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Work with text (with textbook, with book), Methods of individual activities, Skills training
  • Writing a seminar paper - 52 hours per semester
  • Contact teaching - 52 hours per semester
  • Home preparation for classes - 12 hours per semester
  • Preparation for an exam - 24 hours per semester
  • Preparation of a presentation (report) - 10 hours per semester
Learning outcomes
The aim of the course is to provide students with the theoretical and mathematical basics needed to use statistical methods in quantitative research. Emphasis is placed on practical skills, i.e. on data processing in IBM SPSS Statistics software and subsequent interpretation and presentation of results.
Students are able to orientate themselves in basic statistical characteristics and use basic and advanced statistical methods of data processing using SPSS Statistics software. They are competent to design and implement appropriate data acquisition, processing, analysis, interpretation and presentation of results.
Prerequisites
The study of the subject does not require any prerequisites.

Assessment methods and criteria
Written examination, Home assignment evaluation, Presentation

Written exam, elaboration and presentation of seminar paper.
Recommended literature
  • Carver, R. H., Nash, J. G. Doing Data Analysis with SPSS. Pacific Grove: Brooks-Cole Publishing, 2012.
  • Field, A. Discovering Statistics Using IBM SPSS Statistics. 4. vyd. London: SAGE Publications, 2013.
  • Hendl, J. a kol. Statistika v aplikacích. Praha: Portál, 2014.
  • Hendl, J. Přehled statistických metod. 4. vyd. Praha: Portál, 2012.
  • Meloun, M., Militký, J. Interaktivní statistická analýza dat. 3. vyd. Praha: Karolinum, 2012.
  • Paták, M. Materiály ke cvičením z předmětu ?Statistická analýza výzkumných dat?. Materiály dostupné v systému STAG. Univerzita Pardubice, 2017.
  • Paták, M. Statistická analýza výzkumných dat. PPT prezentace dostupné v systému STAG. Univerzita Pardubice, 2017.
  • Řezanková, H. Analýza dat z dotazníkových šetření. 2. vyd. Praha: Professional Publishing, 2010.
  • Vlčková, V., Machač, O., Paták, M. Aplikovaná statistika. Pardubice: Univerzita Pardubice, 2013.


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