Statistical Methods

These pages have some introductions to a wide range of commonly used statistical analyses in the environmental sciences.

Some simple hypothesis tests with the t statistic:

• One sample t tests - contrasting a single sample parameter to a population parameter
  
• Independent samples - contrasting the means of two samples
• Paired t-tests - contrasting two groups when data are paired

Linear models:

• Linear regression
• Analysis of variance: single factor
• Analysis of variance: factorial
  
• Understanding interactions

Generalised linear models:

• Generalised linear models 1: Introduction and binomial data
  
• Generalised linear models 2: Count data

Mixed models:

• Mixed models 1: Linear mixed models with one random effect
  
• Mixed models 2: Linear mixed models with several random effects
  
• Mixed models 3: Generalised linear mixed models

Generalised additive models

Categorical data analyses:

• Goodness of fit tests
  
• Contingency tables

Power analyses: calculating power and deciding on sample sizes

Introduction to mvabund: model-based analysis of multivariate abundance data

Forecasting with time series

Meta-analyses

• Meta-analyses 1: Introduction and calculating effect sizes
  
• Meta-analyses 2: Fixed effect and random effect models
  
• Meta-analyses 3: More complex models