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Lecturer(s)
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Sigmund Erik, prof. Mgr. Ph.D.
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Kolarčik Peter, Mgr.
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Course content
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unspecified
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Learning activities and teaching methods
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unspecified
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Learning outcomes
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The course serves as an introduction to statistical data analysis, where students will be introduced to fundamental concepts essential for understanding research and basic statistical findings. Topics will include statistical significance, hypothesis, statistical power, effect size, statistical description, statistical inference, hypothesis testing, and relationship analysis. Theoretical knowledge will be complemented by practical examples of statistical data analysis using IBM SPSS software.
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Prerequisites
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Required reading: Field, O. (2013). Discovering Statistics Using IBM SPSS Statistics. Sage Publications. Reccomended reading: Byrne, B. M. (2009). Structural Equation Modeling With AMOS: Basic Concepts, Applications, and Programming. Second Edition (Multivariate Applications Series). Routlege.
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Assessment methods and criteria
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unspecified
Required reading: Field, O. (2013). Discovering Statistics Using IBM SPSS Statistics. Sage Publications. Recommended reading: Byrne, B. M. (2009). Structural Equation Modeling With AMOS: Basic Concepts, Applications, and Programming. Second Edition (Multivariate Applications Series). Routlege.
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Recommended literature
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