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Description
鈥楥omputational Biology鈥� introduces the students to advanced statistics, applied to the biological sciences. It builds on first year modules (mainly Quantitative Biology and Methods in Ecology and Evolution) and introduces more advanced linear and generalised linear models, as well as approaches to model building and comparison. It also covers applications of linear models to large-scale genomic data, programming, permutation-based tests, power analysis and multivariate statistics.
In addition to providing the theoretical background of the approaches covered, the module puts much emphasis on practical implementation. Lectures are accompanied by weekly practical sessions in which you will work through analyses in the statistical software R, the standard in many areas of biology.
The module is assessed via online quizzes and two homework assignments. The quizzes focus on theoretical knowledge and the use of R. The homework assignments give you the opportunity to independently analyse larger datasets, interpret the results and write up your methods and findings in publication format.
Overall, this module will provide you with analytical skills that are essential for research across disciplines of biology and other branches of science and professional activities.
Indicative lecture topics and learning objectives:
- Basic programming in R
- Introduction to probability
- Regression and linear models
- Analysis of Variance
- Multiple Regression and model diagnostics
- Model comparison
- Logistic regression, Generalized Linear Models
- Statistical power and simulation
- Matrices
Module deliveries for 2024/25 academic year
Last updated
This module description was last updated on 8th April 2024.
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