BCB744 Biostatistics

1 Welcome

This section organises the BCB744 biostatistics material into a coherent sequence, from statistical foundations through hypothesis testing, regression, model extensions, and reproducible analysis.

Use the broader module page for timetable, assessment, and module-wide context:

• BCB744 Module Overview
• Biostatistics Self-Assessment

1.1 What This Section Does

The biostatistics block is designed to help you reason carefully from biological questions to defensible analysis. The emphasis is on choosing appropriate methods, checking assumptions, interpreting model output, and communicating results with scientific discipline.

By the end of this section you should be able to:

• describe data clearly and visualise important patterns;
• choose appropriate inferential tools for common biological questions;
• fit and interpret linear and generalised models;
• diagnose model assumptions and limitations; and
• connect statistical workflow to reproducible scientific practice.

1.2 Section Structure

The biostatistics sequence is organised into five parts:

1. statistical thinking and data foundations,
2. core hypothesis tests,
3. regression and model building,
4. dependence and model extensions, and
5. reproducible practice.

1.3 Suggested Route Through the Material

If you are moving through the course linearly, begin here:

1. The Statistical Landscape
2. Summarising Biological Data
3. Visualising Data
4. Distributions, Sampling, and Uncertainty

Then continue through inference and modelling:

1. Statistical Inference
2. Assumptions and Transformations
3. t-Tests
4. ANOVA
5. Correlation and Association
6. Choosing the Right Test

Then work through the modelling sequence:

1. Simple Linear Regression
2. Polynomial Regression
3. Multiple Regression and Model Specification
4. Interaction Effects
5. Collinearity, Confounding, and Measurement Error
6. Model Checking and Evaluation

Then complete the extensions block:

1. Pseudoreplication
2. Dependence and Mixed Models
3. Generalised Linear Models
4. Generalised Additive Models
5. Nonlinear Regression
6. Quantile Regression
7. Prediction and Explanation
8. Regularisation
9. Reproducible Workflow

1.4 Assessment and Practice

Use these pages alongside the chapter sequence:

• Biostatistics Self-Assessment
• Biostatistics Example 1