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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.-2. Descriptive statistics and graphical presentation of various types of data. 3.-4. Rules of hypothesis testing. Statistical significance. 5.-7. Contingency of categorical data: crosstabulations. Chi square test. 8.-9. Continuous data tests: t-tests.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Demonstration, E-learning, Work with multi-media resources (texts, internet, IT technologies), Individual tutoring
- Class attendance
- 5 hours per semester
- Preparation for classes
- 30 hours per semester
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Learning outcomes
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Descriptive statistics and graphical presentation of various types of data. Rules of hypothesis testing. Statistical significance.
After having successfully completed the subject the student should be able to design statistic investigation and orientate themselves in statistic data analysis and in statistic hypothesis testing.
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Prerequisites
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Knowledge of basic high-school mathematics, work in MS Excel.
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Assessment methods and criteria
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Oral examination, Analysis of student's work activities (technical works)
Oral or practical 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. , 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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