Module Information

Module Identifier
Module Title
Statistics for Experimental Scientists
Academic Year
Semester 1 (Taught over 2 semesters)
Other Staff

Course Delivery



Assessment Type Assessment length / details Proportion
Semester Assessment 10 x online assessments  50%
Semester Assessment Quantitative Research Report  50%
Supplementary Assessment Retake failed elements of the module 

Learning Outcomes

On successful completion of this module students should be able to:

1. Identify appropriate methods of analysis for different types of data.
2. Analyse data using a range of statistical analyses.
3. Interpret the results of data analyses.
4. Apply statistical knowledge in the content of postgraduate research.

Brief description

The module is comprised of a series of self-contained, e-learning based units delivered entirely through Blackboard but supported by optional workshops to provide help as required. A core of compulsory units will reinforce elements of basic statistics while a broader range of more advanced techniques will be available for students to select from according to study scheme and dissertation topic. The statistical techniques will be demonstrated using SPSS, a statistical package fully supported by the University.


An understanding of the principles of research design, the ability to statistically analyse data and the subsequent interpretation of such analyses are essential for Masters courses in Biological Sciences. This module builds on basic statistical principles that would have been covered at undergraduate level and develops procedures relevant to the specific MSc subject areas taught within IBERS, including: animal sciences, equine sciences, ecology.


The module will consist of ten, self contained units each comprised of: Panopto video(s), describing and demonstrating a specific statistical procedure, written instructional material, relevant publications and articles, formative quizzes with feedback that can be attempted any number of times and a final summative quiz which is assessed, can only be attempted once and is time limited.

All students will undertake a core of six units reinforcing basic statistical procedures:

1. Data handling and presentation
2. T-tests
4. Post-hoc significance tests
5. Correlation/Regression
6. Non-parametric tests

Students will choose a further four units from a range of more advanced subject areas including the following:

Multifactorial ANOVA
Repeated measures/Split plot ANOVA
Multivariate Analysis of Variance (MANOVA)
Principal Component Analysis (PCA)
Canonical Variate Analysis (CVA)
Discriminant Function Analysis (DFA)
Survey/questionnaire design and analysis


This module is at CQFW Level 7