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Lecturer(s)
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Fačevicová Kamila, Mgr. Ph.D.
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Jašková Paulína, Mgr.
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Course content
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1. Basic distributions (N, t, F, chi-square). 2. Points and interval estimations. 3. Testing of hypothesis (Student's t-test, F-test) 4. Normality - analytical graphs and tests. 5. Nonparametric tests (Sign test, Wilcoxon test) 6. Contingency tables. 7. Linear regression.
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Learning activities and teaching methods
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Dialogic Lecture (Discussion, Dialog, Brainstorming), Demonstration
- Attendace
- 26 hours per semester
- Homework for Teaching
- 30 hours per semester
- Semestral Work
- 30 hours per semester
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Learning outcomes
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Statistical software R and SAS EG - testing of normality, testing of hypothesis and parameters estimation, tests in contingency tables, linear regression.
Knowledge - Knowledge of procedures and functions for basic parametric and nonparametric methods.
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Prerequisites
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Basic knowledge of software R and SAS EG (data import and manipulations, summarization and data presentation).
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Assessment methods and criteria
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Student performance
Each student has to create a document with examples from seminars and homework.
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Recommended literature
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Online dokumentace softwaru R.
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A. Field, G. Miles. (2010). Discovering Statistics Using SAS. London.
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J. Verzani. (2005). Using R for Introductory Statistics.
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P. Murrell. (2006). R Graphics.
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R. M. Heiberger, B. Holland. (2004). Statistical Analysis and Data Display: An Intermediate Course with Examples in S-Plus, R, and SAS. Springer Texts in Statistics, Springer.
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