Module 12: Fundamental Statistical Tools

About the course

A good working knowledge of statistics can help you achieve better study designs, choose the correct analytical framework, and present your results in a meaningful way. In conservation, statistics is crucial for making decisions and predictions based on data. Module 12 aims to provide an understanding of fundamental statistical tools, and how to implement them in the widely used R software. All sessions include practical exercises that will help you become familiar with the R language.

    • Session 1

All statistical endeavours start with data. In this session, you will learn how to import your data into the R environment. This will be the perfect opportunity for you to become familiar with the R language, as well as with its basic commands. You will learn about data types most commonly used by ecologists, and the basics of descriptive statistics.

    • Session 2

In this session, we explore in more details the fundamentals of statistical theory. Using built-in datasets in R, you will learn how to identify methods that are most appropriate depending on the data you are working with, as well as essential principles of hypothesis testing.

    • Session 3

Using what we learned in the previous two sessions, we will work through all essential steps involved in data analysis, with a focus on linear regression. This includes the formulation of a hypothesis, data preparation and visualisation, statistical testing, and finally, results interpretation. We will complete two full practical exercises in R using built-in datasets. At the end of this session, you will be split into different groups in order to carry out one final analysis, which will be presented the week after.

    • Session 4

This session will start with presentation of results from the last analysis (see Session 3). The rest of the session will be dedicated to identifying and avoiding common mistakes in data analysis. This will allow us to also discuss issues related to results interpretation, which is essential in the field of conservation science when results may directly inform conservation planning.

Skills you will gain

    • How to organise your data
    • Hypothesis testing
    • Linear regression
    • Interpretation of results
    • How to avoid common mistakes

Meet the Resource Team

Anne Heloise Theo is a marine ecologist working on community ecology and behaviour of reef fish. She is currently a PhD student in the Centre for Ecological Sciences, Indian Institute of Science.

Guillaume Demare is a PhD candidate at the Museum für Naturkunde Berlin, Germany. His research currently focuses on the community ecology of West African amphibians.


  • Thursdays June 3rd, 10th, 17th, 24th 2021
  • 14:00-16:30 Bishkek time (2.5 hour)

Criteria for participation

  • Snow Leopard Network Member
  • Confirmed availability to attend all the four online seminars of a given module
  • Number of participants is limited to 25

Planned Schedule

  • 2.5 hour online Zoom Seminars take place Thursday of the month, June 2021 at 14:00 Bishkek, Kyrgyzstan time.
  • Additional group work, assignments or readings are likely to be organized by the trainers
  • Please note we expect all participants to attend the complete set of Thursday Seminars as they are interconnected and build on each other
  • Details of each specific Seminar topic will be shared approximately 5 days beforehand; including any expected preparations by participants.
  • Please note that all sessions are recorded and then made available online through the SLN youtube channel. By participating in these online sessions you automatically agree to authorise recording of audio and visual content presented during the live event and consent to subsequent use of the recording in the public domain by SLN. If you have any concerns please contact us. 

Deadline for Applications

  • May 26th, 2021. Please note places are limited so please do
    not delay in applying.
  • Applications Closed


Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.