Statistical tools are at the core of scientific progress. Essentially every publication in the empirical
life sciences today conducts statistical tests. To critically assess the validity of the results some basic
statistical knowledge is necessary. This two-day workshop of “Basics in Statistics” has the aim to
teach this knowledge and to provide the participants with tools to decide which statistical tests are
appropriate to use in which contexts.
The workshop will start with a general introduction to statistics and descriptive statistics. The
philosophy of hypothesis testing will be covered and the most common tests for a variety of
(relatively) simple experimental designs will be explained: chi-squared, t-test and ANOVA, as well
as their non-parametric alternatives. Additionally, I will explain the basics of linear regression to
show how correlations, or possibly even causation, between variables can be explored.
No prior knowledge is necessary to take this course. Code examples will be provided in the
programming language R, but no programming knowledge will be assumed, nor is the aim of the
course to teach a specific computational tool to conduct the statistical tests.
Instructor: Pete Czuppon, Institute for Evolution & Biodiversity, University of Münster
05.-06.December
First day: 09 am - 12 am
Second day: 12 am - 06 pm
Multiscale Imaging Centre, Room 223, 2nd floor