BI3010: Statistical Analysis of Biological Data

Overview

This 3rd year undergraduate course introduces students to key statistical theory and data analysis techniques in biological sciences. It makes strong use of R and ggplot2 but aims to give a strong fundamental and theoretical understanding of statistical modelling and associated topics.

Topics Covered

  • Why do we need statistics?
  • Introduction to linear models (LM) and hidden assumptions
  • The theory of effective data visualisation
  • R and ggplot2
  • LMs with a continuous predictor
  • Interpreting LMs with a continuous predictor
  • Assessing assumptions of LMs with a continuous predictor
  • LMs with a categorical predictor
  • Interpreting LMs with a categorical predictor
  • Assessing assumptions of LMs with a categorical predictor
  • LMs with multiple predictors
  • Confounding and causality
  • Null Hypothesis Significance Testing and P-values
  • An Information Criterion (AIC)
  • An introduction to GLMs
  • Poisson GLMs




What students learn




Tools & Software

  • R
  • RStudio
  • ggplot2

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