BIOL40390 Quantitative Tools for the Life Sciences

Academic Year 2022/2023

This module aims to equip you with the skills to professionally interpret and communicate technical information in the biological and biomedical sciences.

Topics covered include data management, data visualisation, design and analysis of biological experiments, introduction to linear models and hypothesis testing using the R statistical software package.

Students will require their own laptops for this module.

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Curricular information is subject to change

Learning Outcomes:

Students will:
1. Design a biological experiment, taking due account of independence, allocation of replicates and controls;
2. Organise and manipulate data on a computer;
3. Fit and validate a statistical model to biological data;
4. Test a null-hypothesis using fitted statistical models;
5. Answer research questions and draw strong defensible conclusions using statistical data analysis;
6. Professionally report the conclusions from a data analysis project.

The module will contribute towards the development of the following skills:
• Working effectively within a team
• Effective presentation and writing of technical information
• Transparency and collaboration on data analysis projects
• R statistical language and general computer skills

Student Effort Hours: 
Student Effort Type Hours




Autonomous Student Learning


Online Learning




Approaches to Teaching and Learning:
A mixture of online learning, with lectures and practical sessions 
Requirements, Exclusions and Recommendations
Learning Recommendations:

Basic computer literacy (e.g. Excel and Word).

Module Requisites and Incompatibles
Not applicable to this module.
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Assignment: R script to accompany the online test Unspecified n/a Graded No


Class Test: Online Tests Varies over the Trimester n/a Alternative linear conversion grade scale 40% No


Assignment: Project report (submitted at the end of module) Unspecified n/a Graded No


Carry forward of passed components
Remediation Type Remediation Timing
In-Module Resit Prior to relevant Programme Exam Board
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Beckerman, Childs and Petchey (2017) Getting started with R : an introduction for biologists (Oxford University Press, Oxford) [electronic resource]

Crawley (2015) Statistics : an introduction using R (John Wiley & Sons, Ltd, London) [electronic resource]

Raykov and Marcoulides (2013) Basic statistics : an introduction with R (Rowman & Littlefield Publishers, Inc., Plymouth). [electronic resource]

Barnard, Gilbert and McGregor (2011) Asking questions in biology: a guide to hypothesis testing, experimental design and presentation in practical work and research projects (Pearson) [electronic resource]

Ruxton and Colegrave (2016) Experimental design for the life sciences (Oxford University Press, Oxford)

Underwood AJ (1997) Experiments in ecology: their logical design and interpretation using analysis of variance. (Cambridge University Press, Cambridge).

Name Role
Professor Tasman Crowe Lecturer / Co-Lecturer
Dr Joanna Kacprzyk Lecturer / Co-Lecturer