Syllabus

Introduction, basic concepts from probability theory

Origin and importance of statistics, descriptive and mathematical statistics, usage in pharmacy. Probability – selected topics that are important for statistics and its understanding. Main parameters of for statistical data sets.

Basic distributions

The normal distribution and the central limit effect. T-distribution, sampling and statistical independence, correlatoin. Chi-square and F-distribution.

Introduction to hypothesis testing

Reference distribution, one- and twosided tests, randomization and permutation tests. Z-tests a various types of t-tests, F-test for equal variances, chi-square test of independence (Pearson‘s chi-square test).

Interval estimates of parameters

The basic idea of the most common interval estimates. Relation with hypothesis testing.

ANOVA

Analysis of variance for one and more factors. Decomposition of variability using several types of sums of squares (ANOVA tabels).

Regression models

Their purpose and ways to use them. Linear regression and logistic regression.

Nonparametric methods

Principles and ways to use them. Selected methods (interval estimates and hypothesis testing), their application and interpretation of the results. Rank-sum test (Mann-Whitney U-test), Wilcoxon test, Kruskal-Wallis test.

Summary – planning a statistical experiment

Selection of the method, verification of assumptions, determining the sample size and the relation to statistical power, outlier detection, presentation of results.