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The University of Southampton

BIOL2008 Quantitative Methods in Biological and Environmental Science

Module Overview

This module develops analytical skills required for the final year Honours Project, scientific research in general, and your future career. The major skills are computer literacy and graphical presentation, understanding of scientific method and hypothesis testing, a few simple mathematical concepts, and basic methods of statistical analysis, including non-parametric tests, analysis of variance and data modelling.

Aims and Objectives

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

  • Outline the nature of scientific knowledge and the processes of framing and testing hypotheses.
  • Draw conclusions from the outputs of statistical analyses.
  • Explain the concepts of the null hypothesis, p-value, statistical power, type I & II errors, significance and non-significance, and draw appropriate conclusions for the hypotheses being tested.
  • Enter data into the open-source R environment, check for errors, write and use R scripts, and plot, label and annotate graphs.
  • Calculate logarithms and other simple transformations and the equation of a straight line.
  • Calculate the mean, median, mode, standard deviation, standard error, confidence intervals and inter-quartile ranges of a sample.
  • Explain the difference between parametric and non-parametric statistics, and the assumptions that underlie them.
  • Choose the appropriate statistical test for a variety of simple problems, and plan and design experiments before collecting data, taking account of the statistical techniques you will use.
  • Use a statistical model in R to make a statement about predicted relationships.
  • Perform simple non-parametric and parametric statistical tests of dependency, variance and correlation, using the R environment


Scientific method and theories, hypothesis testing, biological data, simple data handling and spreadsheets, graphics and report writing, simple statistical tests, non-parametric tests, contingency tests, multivariate methods, one-way and two-way analysis of variance, statistical modelling, regression and correlation, how to plan an analysis and choose an appropriate test.

Learning and Teaching

Teaching and learning methods

Teaching and learning will involve lectures, measurement of biological samples, computer-based practicals.

Practical classes and workshops20
Independent Study107
Total study time150

Resources & Reading list

Dytham, C (2011). Choosing and Using Statistices: A Biologist's guide. 



MethodPercentage contribution
Assignment 25%
Assignment 25%
Class practicals 20%
Class practicals 15%
Class practicals 15%


MethodPercentage contribution
Assessment 60%
Coursework 40%

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