This course teaches the basic principles of all statistical tests and will enable participants to choose suitable statistical tests, carry them out properly and evaluate the results with expertise.
- Basics of statistical estimation and testing (brief revision/refresher course), data types (metric/quantal), confidence intervals, hypotheses, significance level, tailedness, probability distributions, significance level
- Statistical testing, preliminary tests on anomalies, normal distribution and homoscedasticity, selection criteria for tests, pairwise comparison, i.e. statistical comparison of two test approaches, general evidence of an effect (ANOVA), determining the critical threshold concentrations via multiple tests (NOEC), criteria for assessing significance (power of a test)
- Curve fitting, data modelling, analysis of dose-response relationships, linear regression (probit, logit, Weibull), criteria for assessing goodness of fit, non-linear regression, alternative methods
- Comparison of ECx and NOEC