Summary:
This course provides a basic introduction to medical statistics reaching from study design to statistical testing and basic regression models. The exercises cover theoretical aspects as well as practical examples using the software MATLAB.
Topics:
- Types of Data
- Uncertainty, types of noise (random noise, biological noise), bias
- Study design, randomization
- Probability distributions, density functions, central limit theorems
- Concepts of descriptive statistics (median, mean, curtosis etc.)
- Diagnostic tests, sensitivity, specificity, ROC, positive predictive value, negative predictive value
- Concepts of statistical testing, p-values, errors of first and second kind, power
- Multiple testing
- Specific statistical tests, e.g., t-tests, ranksum test, kolmogorov smirnov test, chi-square test, binomialtest
- Anova
- Sample size calculation (for t-test, ranksum-test)
- Propensity score matching (optional)
- linear regression
- logistic regression
- Cox-regression
- Kaplan-Meier analysis, logrank-test
- Kullback- Leibler Divergence and related approaches (optional)
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