Statistical Methods in Natural Sciences

Program: Master programme in Biology
Level: Advanced level
Course code: 1BG391
Credits: 5 hp
More info: Course syllabus
Student portal: Schedule and course material

Part-time course (Tuesdays and Thursdays 1PM - 3PM) running from late January - late March. The course is given in English.

Statistical Methods in Natural Sciences is an advanced course covering the most commonly applied modern statistical techniques and tools used in science. In addition to providing you with an overview of the statistical “tool-box”, the course aims at giving an understanding of the philosophy and reasoning behind statistical design and inference.

The course is a combined master-PhD level course and is recommended for students doing their degree project with own data to analyse. The course requires that students have an understanding of basic statistical concepts (estimation of means, standard errors, confidence intervals, etc.).

Course content: Experimental designs leading to ANOVA or ANCOVA, including block experiments, repeated measurement designs, nested and factorial designs. Multiple regression, including techniques for selecting variables and evaluating models. Generalized linear models (GLIM) with logistic and Poisson regression. Introduction to power analysis, multivariate analysis, resampling and permutation techniques.

A short introduction to the free software R will also be included, although the course is not built on a particular piece of software. Practicals are an integral part of the course.

Course literature: Quinn, G, & Keough, M. 2002. Experimental Design and Data Analysis for Biologists, Cambridge University Press

For more info contact:
Göran Arnqvist (