We offer a live, instructor-led, distance-learning course based around our book An Introduction to Making Graphs and Maps 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 make high quality and informative graphs and maps based on biological data using R. This includes making graphs using the GGPlot package, making bar graphs of count data, making graphs of summary statistics (such as mean values) with error bars, making point graphs of summary statistics for two variables with vertical and horizontal error bars, making box plots, making X-Y scatter plots of individual data points, making line graphs of time series data, making pair-plot matrices of environmental variables, making simple X-Y plots of tracking data and making maps from biological data in R. In addition, you will learn how to use a variety of different R packages and how to create workflows for making any type of graph, map or data visualisation in R.
We will next be running this course 25th – 28th March 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 Making Graphs and Maps for Biologists using R. As a result, all participants will receive a free copy of this book shipped to their address as part of the cost 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 Making Graphs and Maps 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 info@GISinEcology.com.
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).
This course will cover:
- An introduction to R and RStudio (and, if required, this will include help with installing these software packages).
- What you need to know to get started with using R.
- How to create your first graphs in R using GGPlot.
- How to create graphs displaying groups of data with GGPlot.
- How to create graphs displaying individual datra points with GGPlot
- How to create maps from biological data using R.
- How to work out how to do things in R.
- How to create an annotated R code archive so you have a record of what you have done.