Data Analysis for Conservation Biologists - WCON5380

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Module delivery information

This module is not currently running in 2024 to 2025.


This module is designed to introduce and re-affirm statistical concepts and their correct use and relevance to field biologists. It is delivered through a combination of lectures on statistical practical tasks and exercises.

Introductory topics will include:
• measures of central tendency
• frequency distributions
• the normal distribution
• standard errors
• how sample parameters and null hypotheses apply in real biological situations.

Further topics will include
• one- and two-tailed tests
• chi-squared test
• regression analysis
• analysis of variance.

The role of probability in data analysis will be considered, as will its application to biological and ecological questions. Throughout, emphasis will be placed on practical application of statistics as much as possible, and when and how they are applied.

Since there is both a theoretical and practical component, students should aim to link the theory presented in lectures with the practical sessions and field trip components. The field trip will be towards the end, by which time you will have been exposed to sufficient statistical methods and be ready to apply them.

By the end of the module you should have a knowledge of the underlying principles of statistics, be able to evaluate statistical results from a theoretical standpoint and in practice, and have a sound appreciation of the benefits and limitations of different statistical techniques and their application. This module provides you with the statistical knowledge to conduct the data analysis for your research project, and to reinforce the appreciation and knowledge of statistical methods.


Contact hours

Total contact hours: 24
Private study hours: 126
Total study hours: 150


Compulsory to:
• BSc Wildlife Conservation

May be offered as optional on:
• BA Environmental Social Sciences
• BSc Human Geography

Not available as an elective module.

Method of assessment

Main assessment methods:
Statistics worksheet (40%)
Full statistics write-up and paper (60%)

Reassessment method: 100% coursework.

Indicative reading

Reading list (Indicative list, current at time of publication. Reading lists will be published annually)

• Fowler, J., Cohen, L. & Jarvis, P. (1998). Practical Statistics for Field Biology. John Wiley & Sons. Chichester, UK.

• Ruxton, G. D. & Colegrave, N. (2003). Experimental Design for the Life Sciences. Oxford University Press.

Learning outcomes

Subject specific learning outcomes. On successfully completing the module you will be able to:
1. Discuss the theoretical normal distribution, and its application to data analysis.
2. Discuss null hypotheses, type I and II errors, sample strategies, and independence
3. Discuss and use parametric and non-parametric tests, including t-tests, Mann-Whitney, Chi-Square, Analysis of Variance (ANOVA) and Kruskal-Wallis, regressions and correlations.

Generic learning outcomes. On successfully completing the module you will be able to:
1. Understand, analyse and re-affirm statistical concepts, and their correct use and relevance
2. Understand topics including measures of central tendency, frequency distributions, the normal distribution, standard errors, and how sample parameters, and null hypotheses apply
3. Understand how to compare for statistical differences, and for statistical relationships
4. Understand the role of probability in statistics.


  1. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
  2. The named convenor is the convenor for the current academic session.
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