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Lecturer(s)
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Navrátil Josef, doc. RNDr. Ph.D.
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Course content
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1. Data types 2. Basic data processing: position and variability characteristics 3. Frequency characteristics 4. Probability and hypothesis testing 5. Parametric tests: normal distribution, one-sample t-test 6. Parametric tests: two samples (paired t-test, two-sample t-test, F-test) 7. Continuous test 8. Goodness of fit test, Fisher's exact test, Kolmogorov-Smirn test 9. Nonparametric comparison of two selections: Mann-Whitney test, Wilcoxon test 10. Multiple selections: One-factor ANOVA, Kruskal-Wallis test 11. Covariance and correlation 12. Linear regression 13. Credit For KS, the above topics will be grouped according to the current settings of the consultation schedule.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Demonstration, Laboratory
- Class attendance
- 42 hours per semester
- Preparation for exam
- 42 hours per semester
- Preparation for credit
- 22 hours per semester
- Preparation for classes
- 19 hours per semester
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Learning outcomes
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The aim of the course is to acquaint students with the introductory principles of quantitative data evaluation. The main concepts of one-dimensional data analysis with practice of practical analytical procedures in solving partial problems using MS Excel and R will be presented.
Students are able to evaluate nominal, ordinal and ratio data using basic methods, test one-dimensional hypotheses and assess the tightness of the relationship between variables.
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Prerequisites
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Knowledge of basic mathematical operations. Ability to work with PC
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Assessment methods and criteria
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Written examination
Credit requirements: 1. Proof of student card (= index). 2. Personal participation in seminars, two absences are allowed (does not apply to KS). 3. Credit test passed at least 60% in total. The credit form consists of two parts in the standard form - 6 tasks in the so-called midterm exam and 4 tasks in the credit week (for KS both within the deadline agreed for the 1st consultation). Both tests are electronic, MS Excel and R software. tests, F test; and in the credit week, hypothesis testing, chi-square test, Fisher's exact test, Mann-Whitney test, Wilcoxon test, one-factor ANOVA, Kruskal-Wallis test, covariance calculation, correlation and regression. Note for PS: If you did not pass the "midterm exam" due to your absence, then you will pass it together with the 2nd credit test in the credit week. If you do not get at least 60% in the sum of the "midterm exam" and the 2nd credit test, you must pass both tests together in the corrected term - you have two corrective terms (applies to PS and KS). Exam requirements: 1. Pass a test at least 60%. The exam is focused on theoretical knowledge, it asks 14 questions. 10 questions always have four possible answers (just one of them is correct) - the body gets a point for the correct answer, the body is not deducted for incorrect answers, 4 questions are with a free answer, a point is awarded for the correct answer. The optional written part of the exam is followed by an optional oral part. 2. Proof of student ID (= index).
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Recommended literature
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Lepš J.:. Biostatistika. Biologická fakulta JU. 1996.
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Meloun, M., Militký, J. Kompendium statistického zpracování dat. Praha : Academia. 982 s., 2006.
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Zvára, K.:. Biostatistika. 2. vyd. Praha: Karolinum, 2004. ISBN 80-246-0739-5.
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