Statistics Courses

The division of Biostatistics offers three consecutive statistics lecture series starting every summer semester.The aim of the courses is to enable the participants to perform simple analyses by themselves, to recognize when professional statistical advice is needed and to facilitate cooperation between researchers and the division of Biostatistics. The topics that are covered are chosen according to the needs of researchers at the DKFZ. The lectures are held weekly during both the summer and winter terms and last one hour. For details about dates and location please visit the HCM-Portal (for DKFZ employees on the intranet), the Heidelberg University Lecture Index, or contact the division of Biostatistics.

Basic Principles of Biostatistics (summer term)

Lecture series for researchers and PhD students in the biological or clinical sciences without prior knowledge in statistics.


  • Descriptive statistics: plots, measures of location and spread
  • Confidence intervals
  • Statistical hypothesis testing, p-value, etc.
  • Statistical tests for quantitative data, e.g., t-test
  • Statistical tests for qualitative data, e.g., chi-square test
  • Correlation and regression
  • Study design

Advanced Topics in Biostatistics (winter term)

Team-taught lecture series by members of the division of Biostatistics for researchers and PhD students in the biological or clinical sciences with basic knowledge of statistics.


  • Multiple linear regression
  • Analysis of Variance
  • Logistic regression
  • Diagnostic tests
  • Dose-response modeling
  • Non-parametric methods
  • Survival analysis: Kaplan-Meier curves, logrank tests, Cox PH regression
  • Multiple Testing
  • Data quality and validation, missing values
  • Statistical issues in bioinformatics:
    • Differential gene expression and group tests
    • Unsupervised learning and visualization
    • Supervised learning
  • Validation of statistical models: Cross-validation, bootstrapping & Co
  • Design of clinical and epidemiological trials

Biostatistical Case Studies using R and Bioconductor (summer term)

Lecture series by members of the division of Biostatistics, in which the use of the statistical programming language R is demonstrated using real data analyses as examples. This advanced R-course is focused on programming. Participants should be familiar with basic statistical concepts and have some basic R programming skills. Ideally, participants will have attended the lecture series 'Basic Principles of Biostatistics' and 'Advanced Topics in Biostatistics' as well as a beginners R course.


  • Introduction to R, Rstudio and Bioconductor
  • Data quality checking and missing values imputation
  • Case studies on:
    • Parametric versus non-parametric tests
    • ANOVA and multiple comparisons
    • Diagnostic tests and measuring agreement
    • Multiple linear regression and variable selection
    • Survival analysis
    • Classification and model selection with resampling methods
    • Multiple testing and differential gene expression with LIMMA
    • Gene group tests and pathway and gene ontology analyses
    • Clustering and heatmaps
    • Dimension reduction with principal component analysis et al.

In addition to the courses organized by the division of Biostatistics, the Advanced Training department of the DKFZ also offers programming courses in R and SAS, and the Genomics and Proteomics Core Facility at DKFZ offers courses on specific data analysis tools for high-throughput genomics data. DKFZ employees please visit the HCM-Portal for further information. The Institute of Applied Mathematics at Heidelberg University also organizes R-courses; see here for further information.

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