Statistics are an important part of most modern studies and being able to effectively use a statistical package will help you to understand your results.
This course provides an introduction to some statistical techniques through the use of the R language. Topics covered include: Chi2 and Fisher tests, descriptive statistics, t-test, analysis of variance and regression.
Students will run analyses using statistical and graphical skills taught during the session.
Anne Segonds-Pichon, Babraham Institute
Simon Andrews, Babraham Institute
Audience and Prerequisites
- Familiarity with the R language is essential. We recommend attending the An Introduction to Solving Biological Problems with R course prior to attending this course.
- Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
Syllabus, Tools and Resources
During this course you will learn about:
- Classical statistical techniques using a free increasingly popular package like R
After this course you should be able to:
- Discuss basic principles of experimental design and power analysis
- Understand concepts as descriptive parameters such as mean, variance, standard deviation and hypothesis testing
- Use R to apply classical statistical techniques on quantitative and qualitative data