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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. Chi square test. 5.-7. Contingency of cathegorical data: crosstabulations. 8.-9. Continuous data tests: t-tests. Seminars follow up the lectures.
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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
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Learning outcomes
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The goal of the subject is to familiarize the student with fundamentals of statistical methods most frequently used in health and social area. Stress is put on practical mastering of elemental data processing with the help of statistic functions integrated in MS Excel, including the Data Analysis tool.
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)
Students ought to process the supplied data using any software available (MS Excel, IBM SPSS). Second choice is a theoretical 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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