| Detailed information |
| Pre-requisites |
(*)Zulassung zum Doktoratsstudium Medical Sciences
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| Original study plan |
Doctoral programme Medical Sciences 2026W |
| Learning Outcomes |
Competences |
| Students have a sound knowledge of methods for statistical analysis of different response variables (quantitative, binary, survival response). They know basic methods to asses reliability of measurements and properties of diagnostic tests
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| Skills |
Knowledge |
- Compute measures for association
- Compute point estimates and confidence intervals and interpret them
- Perform statistical tests and interpret their results
- Interpret results of linear and logistic regression models
- Interpret results of survival analysis
- Use statistical software to perform statistical analyses
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- Concepts of point and interval estimation
- Concepts of statistical testing and sample size calculation
- Modelling assumptions, estimates and tests for hypotheses on regression effects, as well as basic concepts for residual analysis
- Linear and logistics regression analysis
- Concepts and methods for the analysis of survival data
- Basic concepts of measuring reliability and assessment of diagnostic tests
- Common misuses and misinterpretations of statistical results and how to avoid them
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| Criteria for evaluation |
Attendance of at least 80 %
Students are assessed throughout the course by discussing small homework examples as well as a final presentation.
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| Language |
English and French |
| Study material |
Slides provided by instructor
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| Changing subject? |
No |
| Further information |
Students are required to assess their prior knowledge by completing the online self-assessment test available on the doctoral program’s Moodle page. Students who do not achieve a satisfactory result are expected to attend the preparatory course offered at the beginning of the winter semester, prior to the start of the statistics classes.
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| Is completed if |
(*)405FUSCFS2S23: SE Fundamentals of scientific research and general skills: Basic Statistics (3 ECTS)
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