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Theme: Mathematics & Statistics

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An Introduction to R: Software For Statistical Analysis, with Dr Simon R. White, MRC Biostatistics Unit, and Dr Adam P. Wagner, University of Cambridge.

GNU R is (freely) available for all major platforms (Microsoft Windows, Linux, Mac, etc.) and is growing in popularity in academia and beyond for carrying out statistical analysis and data manipulation.

The aim of the course is to introduce participants to the basics of statistical analysis and the open source statistical software GNU R.

Participants will actively use R throughout the course, during which they will be introduced to principles of statistical thinking and interpretation by example, exercises and discussion about a range of problems. The examples will be used to present a variety of statistical concepts and techniques, with no focus on any specific discipline.

Participants Without a Raven Password: If you do not have a Raven's account and would like to attend this course, or have other booking queries, please email Adam Wagner (apw40@medschl.cam.ac.uk).

Statistics for Biologists in R new Mon 26 Feb 2018   14:00   [More dates...] [Full]

This laptop only course is intended to provide a strong foundation in practical statistics and data analysis using the R software environment. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences.

There are three core goals for this course:

  1. Use R confidently for statistics and data analysis
  2. Be able to analyse datasets using standard statistical techniques
  3. Know which tests are and are not appropriate

R is a free, software environment for statistical and data analysis, with many useful features that promote and facilitate reproducible research.

In this course, we introduce the R language, and cover basic data manipulation and plotting. We then move on to explore classical statistical analysis techniques starting with simple hypothesis testing and building up to generalised linear model analysis. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory

After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.

1 other event...

Date Availability
Mon 15 Jan 2018 14:00 In progress