Course content

Analysis of variance (one- and two-way ANOVA), non-parametric test (Kruskal-Wallis test), correlation and linear regression, logistic regression, survival analysis (Kaplan-Meier plot, log-rank test, Cox PH model).

Learning outcome

After completing the course, the student …
- has achieved theoretical knowledge about statistical methods commonly used within medical research to examine simple and more complex relationships (analyses of variance and covariance, multiple linear and logistic regression analyses, simple and multiple survival analyses)
- can choose statistical method for analyzing data, given scientific question of interest, study design, and characteristics of empirical data (application of theoretical models)
- understands the main principle of estimation and hypothesis testing in relation to the different theoretical models
- Is able to perform the technical work with statistical analyses by means of a statistical program package
- is able to interpret and describe results from statistical analyses of empirical data (application)
- is able to critically evaluate validity of results in view of assumptions on statistical model (application)

Learning methods and activities

Lectures and excercises. Exercises must be passed before admission to examination. The examination may change to an oral exam if few students register.

Compulsory assignments

• Handing in exercise assignment

Recommended previous knowledge

Medical statistics part I or equivalent.

Required previous knowledge

Master degree or similar. Medical students at The Student Research Programme. Candidates with a lower degree will be assessed individually.

Course materials

Rosner, B: "Fundamentals of Biostatistics", 7th ed. 2011 (6th edition from 2006 is sufficient)

Credit reductions