Live Online Course – An Introduction to Basic Statistics for Biologists using R

We offer a live, instructor-led, distance-learning course based around our book An Introduction to Basic Statistics for Biologists using R. It is run over four three-hour sessions via the Zoom video-conferencing platform.

This is a practical course and it is aimed at anyone who wishes to learn how to carry out basic data processing and statistical analyses on biological data using R. This includes importing data sets into R, error-checking and processing them to prepare them for analysis, calculating basic summary statistics, creating graphs, assessing and transforming their distributions, and running statistical tests such as Shapiro-Wilk tests, t-tests, Mann-Whitney U tests, paired t-tests, Wilcoxon Matched Pairs tests, F-tests for equality of variance, Levene’s tests, ANOVAs, Kruskal-Walis tests, chi-squared tests, correlations and linear regressions. It will also cover how to use R, how to work out how to do things for yourself in R and how to create annotated R script archives of what you have done. No previous experience with R or statistical analysis is required to do this course.

We will next be running this course between the 29th January and the 1st of February 2024. It will consist of four three-hour sessions, and one session will need to be completed each day. However, you will have a choice of completing it between 10:00 and 13:00 UK Time (primarily for those living in Europe, Asia and Africa) or 19:00 to 22:00 UK Time (primarily for those living in North and South America). This choice of time slots for each session allows participants from as wide a range of time zones to participate in the course.

Each session will consist of a series of background talk covering specific topics (more details are provided below), followed by related practical exercises based on instructions from An Introduction to Basic Statistics for Biologists using R. As a result, all participants will receive a free copy of this book shipped to their address in advance of the start of the course. While you are encouraged to remain online during the practical sessions, you can choose to go off-line as you work though the exercises (or if you need to take a break). However, if you have any questions, the course instructor will be available throughout the course for you to ask any questions you wish at any point.

This course will be hosted by Dr Colin D. MacLeod one of the authors of An Introduction to Basic Statistics for Biologists using R. Dr MacLeod has been working in biological research for more than 20 years.

At the end of the course, all attendees will receive a certificate of attendance and completion. Each certificate is embossed with the GIS In Ecology official stamp to prevent its fraudulent reproduction. In addition, each certificate has its own unique identification number that we will record, along with your name, meaning that we can verify the authenticity of the certificates we issue (and the course you have completed) on request.

Attendance will be limited to a maximum of 24 people per session. The fees for this course are GBP 295 per person (with a discounted rate of GBP 245 for students, the unwaged and those working for registered charities). To book a place, click on the button below to pay the course fees with a credit/debit card. For more information, or if you would prefer to pay using another method (such as a bank transfer), contact

Please Note: If you choose to pay using the button below, please do not make any arrangements regarding your participation until you have received an email from us confirming your booking for a specific course (this may take a couple of days, depending on how busy we are).

Fee Options

This course will cover:

  1. An introduction to R and RStudio (and, if required, this will include help with installing these software packages).
  2. What you need to know to get started with using R.
  3. What to do if you get stuck with using R for data processing and statistical analysis.
  4. How to import data into R and prepare it for analysis.
  5. How to create graphs from biological data in R.
  6. How to assess and transform the distribution of biological data.
  7. How to compare data from different groups with statistical analysis.
  8. How to use correlations and regressions to biological data.
  9. How to work out how to do things in R.
  10. How to create an annotated R code archive so you have a record of what you have done.