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Statistical analysis using R

 

Description

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. 

 

Trainers

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

 

Learning Objectives

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

 

Links

Book Here

Course materials

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