Module 2, Lecture 5
No Learning Outcomes, but Summary:
• Bayesian and Information Theory approaches: alternatives to null-hypothesis testing
• AIC determines the model of best fit with the number of parameters
• AIC is NOT a measurement of support for a model
• Model averaging recognises uncertainty in models by calculating average parameters weighted by Akaike weights
• Note: CANNOT undo bad sampling or poor experimental design