Statistical Techniques for Computational Scientists

Module Identifier
MAM5220
Module Title
Statistical Techniques for Computational Scientists
Academic Year
2025/2026
Semester
Semester 2
Co-ordinator
Dr Kim Kenobi
Reading List
View on Aspire
Pre-Requisite
MAM5120
Other Staff
Dr Kim Kenobi
Dr Gwion Evans
Miss Sylvia Lutkins

Assessment

Assessment Type

Assessment details

Proportion
Semester Assessment Three practical portfolios 3 x 25%Consultancy exercises 25% (9% for presentation, 16% for essay) 100%
Supplementary Assessment Resubmission of failed components 100%

Learning Outcomes

  1. On completion of this module, students should be able to. Select and apply advanced statistical methods to research problems
  2. Apply the more advanced capabilities of R to analyze complex data
  3. Select and apply advanced statistical methods to research problems
  4. Interpret and report effectively the results of statistical analyses

Brief description

The more advanced capabilities of R will be explored and mastered by applying statistical techniques to problems in Computational Biology.

Aims

This module will allow students to master the more advanced capabilities of R by using them to apply a variety of statistical techniques to problems in Computational Biology. Students are introduced to a variety of new techniques and applications, and proceed to study three of these in depth.
Students will also gain experience of Statistical consultancy.

Content

1. Introduction to a number of advanced topics such as:
MANOVA
Principal Component Analysis
Time series
Epidemiology
Generalised linear models
Transcriptomics

Module skills

Skills type

Skills details
Application of Number Inherent in the study of statistics and statistical methods
Communication Consultancy exercises
Improving own Learning and Performance Awareness of advanced techniques and detailed study of some of these
Information Technology Mastery of the advanced capabilities of R
Personal Development and Career planning Experience of statistical consultancy
Problem solving Identifying and using statistical techniques to solve problems in Computational Biology
Research skills Experimental design
Subject Specific Skills Expertise in advanced analysis techniques
Team work Joint work in consultancy

Notes

This module is at CQFW Level 7