Field Data Experts
Educational Enjoyment
At Eco-Explore, we're more than just educators; we're life scientists passionate about the environment and the natural world. We understand that for many aspiring and current ecologists, the world of data analysis can be as challenging as the terrain we wish to protect. That's why our specialised training programs are crafted to empower you with the analytical tools necessary for ground-breaking work in science and conservation. Every course you take with us not only sharpens your professional edge but also supports the environment directly. Profits from our programs are reinvested into local conservation initiatives—your growth aids the growth of our planet.
Check out our projects to see the tangible impacts of your contributions and how Eco-Explore is turning data analysis into a force for ecological advancement.
Our Courses
Introduction to Data Analysis with R
2 DAY COURSE
11th & 12th February 2025
£200 + VAT (£240)
Our “Introduction to Data Analysis in R” course, perfect for those who have not used R before or those who want to understand linear statistical modelling. Topics include “What is a script file”, “How to install package” up to “Generalised Linear Models using count data”.
Advanced Data Analysis in R
2 DAY COURSE
4th-5th March 2025
£250 + VAT (£300)
Need more advanced statistics? Enrol on our “Advanced Data Analysis in R” course. Topics include “Generalised Linear Mixed Models”, “General Additive Models” and “Zero inflated models”.
“Incredibly knowledgeable teachers with amazing experience of R”
“Excellent step-by-step walkthroughs and explanation of key concepts!”
“Just too good to be true! Already applying these codes to my data set”
“Had not used R before and stats was very rusty, Feel that I can now use R and its similarities/differences to Python and how much better it is a graph visualisation.” –
Guidebook
Our 150-page guidebook is designed to help you quickly to become familiar with R and to explore its potential as a powerful tool for analysing your data, whatever your field of research. The guidebook covers the simple things (getting started with R, plotting graphs, simple statistical tests) as well as more complex topics (e.g. GLM, GAM, GLMM, multivariate data exploration, time-series and survival analysis, spatial analysis).