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Lecturer(s)
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Paták Michal, doc. Ing. Ph.D.
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Course content
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The Importance of Statistics, Basic Concepts, Statistical Software. Analysis of a Population Statistical Dataset. Frequency Tables and Charts. Measures of Central Tendency and Variability, Quantiles. Probability, Random Experiment, Random Variable. Selected Distributions of Discrete and Continuous Random Variables. Analysis of a Sample Statistical Dataset. Point and Interval Estimates. Principles of Statistical Hypothesis Testing. One-Sample t-Test. Paired t-Test. Two-Sample t-Test for Independent Samples. Analysis of Variance (ANOVA). Post Hoc Tests for One-Way Classification,. Analysis of Dependence Between Two Statistical Variables. Correlation Analysis, Covariance and Correlation Coefficient. Regression Analysis. Significance Analysis of the Regression Model and Its Parameters. Coefficient of Determination. Analysis of Dependence in Contingency Tables. Chi-Square Test. Measures of Association and Comparison.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Work with text (with textbook, with book), Skills training, Graphic and art activities
- Independent critical reading
- 22 hours per semester
- Preparation for an exam
- 48 hours per semester
- Participation in classes
- 52 hours per semester
- Preparation for a partial test
- 32 hours per semester
- Home preparation for classes
- 26 hours per semester
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Learning outcomes
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The aim of this subject is to provide students with theoretical and mathematical principles needful for orientation in commonly used statistical characteristics. Emphasis is mainly put on practical skills, i.e. on encompassment of data processing using statistical softwares and on subsequent interpretation and presentation of results.
Student is after fulfillment of this subject able to orientate himself properly in basic statistical characteristics and to use appropriate basic statistical methods of data processing. He is competent to design and to carry out appropriate ways to get data, their processing, analyze, interpretation and presentation of results.
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Prerequisites
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unspecified
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Assessment methods and criteria
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Oral examination, Written examination, Student performance assessment, Discussion
Oral exam, 2 written tests.
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Recommended literature
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Field, A. Discovering Statistics Using IBM SPSS Statistics. 4. vyd. Thousand Oaks: SAGE Publications, 2014. .
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Hindls, R. a kol. Statistika v ekonomii. 1. vyd. Praha: Professional Publishing, 2018. .
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Marek, L. a kol. Statistika v příkladech. 1. vyd. Praha: Professional Publishing, 2013. .
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Paták, M. PPT prezentace dostupné v systému STAG. Univerzita Pardubice, aktuální verze. .
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Rabušič, L. a kol. Statistická analýza sociálněvědních dat (prostřednictvím SPSS). 2. přeprac. vyd. Brno: Masarykova univerzita, 2019. .
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Vlčková, V., Machač, O., Paták, M. Aplikovaná statistika. 1. vyd. Pardubice: Univerzita Pardubice, 2013. .
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