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Lecturer(s)
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Dvořáčková Olga, Mgr. Ph.D.
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Course content
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Lectures: 1. Research projects: research questions, goals and hypotheses 2. Quantitative and qualitative methods 3. Experimental and statistical procedure, sampling 4. Operationalization, measurement and scales 5. Data presentation, basic descriptive statistics 6. Hypotheses testing. Chi-square test 7. Contingency tables 8. Relation and correlation 9. Testing continuous data: t-tests, ANOVA. Nonparametric tests 10. Interpretation - search for the hidden variable 11. Regression and multiple regression 12. Factor analysis 13. Classification and typology (cluster, discriminant analysis) 14. Data validity and reliability, standardization Seminars: 1.-2. Descriptive statistics (incl. graphical representation) of various data types 3. Chi-square test 4.-5. Contingency tables 6.-7. t-tests, ANOVA 8.-9. Nonparametric tests 10.-11. Correlation and regression 12. Multidimensional analyses (FA, CA, DA) 13.-14. Recapitulation
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Demonstration, E-learning, Individual tutoring
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Learning outcomes
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The course is building on the basic methodology knowledge from the bachelor level. It focuses mainly on the advanced techniques of data evaluation. First part of the course (winter semester) deals with quantitative data, second part (summer semester) aims at qualitative research methodology. The goal is to master the skills to acquire and analyze research data at a level needed for a diploma thesis.
Students will be able to design an experimental survey, collect and analyze data and present their findings.
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Prerequisites
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The course is intended for graduate students - some basic level of statistical knowledge is expected. Students are assumed to have a basic knowledge of MS Excel or its alternatives.
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Assessment methods and criteria
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Oral examination, Analysis of student's work activities (technical works)
Students ought to process the supplied data using any software available (MS Excel, IBM SPSS). Second choice is an oral examination.
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Recommended literature
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CARIFIO J., PERLA R. J. Ten Common Misunderstandings, Misconceptions, Persistent Myths and Urban Legends about Likert Scales and Likert Response Formats and their Antidotes. Journal of Social Sciences, 3(3): 106-116. 2007.
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FIELD A. Discovering Statistics Using SPSS. 3. ed. London: Sage Publications, 2009. ISBN 978-1-84787-906-6.
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LIKERT R. A Technique for the Measurement of Attitudes. Archives of Psychology, 22(140): 5-55. 1932.
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OSGOOD C. E., SUCI G. J., TANNENBAUM P. H. The Measurement of Meaning. University of Illinois Press. Urbana, 1957. ISBN 0-252-74539-6.
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