Micro-credential Biostatistics

Beyond the Basics: Advanced Biostatistics in RStudio - Mixed Models, Multivariate Analysis, Bayesian Inference, and Effective Reporting

Description

With advanced statistical methods becoming readily available to everyone, their application and interpretation require a good knowledge of the underlying assumptions of the different techniques. During this course, the similarities and differences between various types of linear models will be explored from an applied point of view. RStudio and the RMarkdown package will be the central software used. Next to the broad group of GLMMs, principles of multivariate statistics, survival analysis, mixtures, and Bayesian inference will be discussed. This collection of statistical methodologies will form a solid basis for everybody active in biosciences who has to perform relatively complex statistical analyses and/or is involved in the interpretation of it.

Program

The biostatistics course focuses on the application of different techniques which biologists often need for their research. The following topics are covered: one-way and two-way analysis of variance, mixed models, regression, multiple regression, analysis of covariance, generalized mixed models (Binomial and Poisson), experimental design, multivariate statistics (principal component analysis, discriminant analysis, correspondence analysis), mixtures, survival analysis and the basic principles of Bayesian statistics.

7 credits