Statistics for Molecular Biomedicine

Knowledge: 

The student will obtain knowledge of

• Statistics for data of biological and/or medical relevance, in particular
  • Descriptive statistics
  • Distributions
  • Study design
  • Hypothesis testing/interval estimation
  • Non-parametric methods
  • Analysis of variance
  • Linear regression
• The symbolic language of statistics and the corresponding formalism
• Interpretation of statistical results for experimental data
• The R program

Skills:

• Set up statistical models for data of biological and/or medical relevance – taking as a starting point models based on the binomial and normal distributions.
• Handle the symbolic language of statistics and the corresponding formalism
• Perform significance testing, p-value calculation and interpretation for simple experimental data, including compute-intensive techniques such as permutation testing.
• Report the results of model set up, data analysis, interpretation and assessment.
• Use R to be able to carry out necessary calculations for the practical statistical analysis of biological data.

Competences:

• Formulate scientific questions in statistical terms.
• Interpret and report the conclusions of a practical statistical analysis.
• Assess and discuss a statistical analysis in a biomedical context.