The course provides an introduction in statistical methodology for life sciences and discusses a number of statistical techniques for practical data analysis. Concrete examples and case studies are used to apply the theory to practical situations.
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This four-day course teaches you the basics in solving your own missing data problems appropriately. Participants will learn how to form imputation models, how to combine data sets, how to model non-response, how to use diagnostics to inspect the imputed values, how to obtain valid inference on incomplete data and how to avoid many of the pitfalls associated with real-life missing data problems.