Lecture 14 Statistics: The Next Generation

• Optional 15 credit second year course
• 11 x (Online lectures, Discussion sessions, Practicals, Help sessions)
• Second semester

• What we taught you is a good basis
• If your experiments are simple, they will be fine
• multiway ANOVAs (with interactions), nested ANOVAs, ANCOVAs etc. etc
• You could learn these piecemeal as required or

• Model formulae
• General and generalised linear models

• 50 male squirrels' weight, 50 female squirrels' weight
• Does the weight of the squirrel depend on its sex?
• Model formula: WEIGHT=SEX
• In R:

WEIGHT~SEX

• ~ means “depends on” (Dependent variable LHS, Independent variables RHS)

• t-tests, ANOVA, ANCOVA, and regressions are types of General linear models
• The difference between general and generalised linear models is simply how error is handled
  • General linear models assume errors are independent and follow a normal distribution
  • Generalized linear models can use a wide range of distributions
  • i.e. your data doesn't have to be normal (bye bye non-parametric tests)
• lm is the R command for General linear models
• glm is the R command for Generalised linear models