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, outlier detection, presentation of results.
Annotation
Applied Statistics addresses basic statistical methods used in pharmacy. It presents an overview of the most common statistical tests and methods, with the emphasis being on the correct choice of a statistical test and the interpretation of its result.
The students are acquainted with the basical statistical functions in commonly available software (mainly in Excel, a brief introduction to GraphPad is planned as well) through practical examples from pharmacy and related fields.