Syllabus
* Mandatory:
FIELD, A.: Discovering statistics using SPSS. London: Sage publications, 2009.
RUMSEY, D. J., & UNGER, D.: U Can: statistics for dummies. New Jersey: John Wiley & Sons. 2015.
* Recommended:
COWLES, M. K.: Categorical Data Analysis. In: Journal of the American Statistical Association Vol. 99, Issue 466, 2004, pp 572-573.
AGRESTI, A.: Wiley Series in Probability and Statistics. Categorical Data Analysis, New York: Wiley-Interscience, Second Edition, 2003, pp 692-699.
Annotation
The aim of the course is to learn practically statistical methods - correlation analysis, regression analysis, statistical comparison of averages of data series - methods most commonly used in bachelor's theses. Syllabus:
1) Introduction
2) Data types
3) Data display, primary, secondary sorting
4) Descriptive statistics
5) Formulation and testing of statistical hypotheses
6) Tests of the equality of two and more means, t-test, ANOVA
7) Analysis of dependencies, correlation
8) Regression analysis
9) Statistical computation of student projects
10) Presentation of student projects
11) Presentation of student projects
12) Presentation of student projects
13) Presentation of student projects