Knowledge and skills in statistics are absolutely essential to researchers working in any field in life sciences, physical sciences or social sciences. Statistics are all about trying to issue trustworthy statements about a reality whose complexity or scale is too big to circumvent experimentally.

In this course we will go through an introduction to various aspects of statistics applied to biomedical sciences. This course will blend formal lectures with a lots of hands-on exercises, all done with the R statistical software.

After the training, you may contact the trainer using the mailing list for this training (“postgraduate2014” at lists.h3abionet.org), or directly at “jeanbaka” at sanbi.ac.za.

## Topics Covered

- introductory probability theory (classic distributions, probability and density functions, moments)
- ongoing tutorial on the usage of R throughout the week
- descriptive statistics (sample estimates, histograms, boxplots)
- inferential statistics: hypothesis testing
- parametric tests on the mean
- non-parametric tests on samples
- goodness-of-fit tests
- chi-square tests on contingency tables

- multivariate analysis
- correlation coefficients and tests
- linear regression
- logistic regression
- Principal Component Analysis

## Expected Outcomes

After the end of this training, students should be able to perform all types of statistical analysis at any point along the chain of biological data processing, e.g. for the analysis of -omics datasets, NGS datasets or results of biomedical studies, etc.