Week 7

Question 1

What is a statistical model?

Answer 1

one or more explanatory variables
(each written as X) and parameters
relating them to the response

Question 2

What is εi?

Answer 2

the unexplained bit (deviation of the observed value of Y from the value predicted by the model)

Question 3

Why are linear models the go-to in biology?

Answer 3

because they’re robust, flexible, and can in principle analyse any response variable

Question 4

What is a generalised linear model?

Answer 4

a linear model that assumes a non-normal distribution

Question 5

What is a plain linear model?

Answer 5

is a
linear model that assumes a
normal distribution

Question 6

What are numerical responses assumed to have?

Answer 6

In practice, we mostly use them to analyse numerical responses that are assumed to have a normal distribution

Question 7

What is µ?

Answer 7

is the overall mean

Question 8

What is Ai?

Answer 8

Ai is the effect of group i in X(µ - µi)

Question 9

what are residuals?

Answer 9

errors are often called residuals

Question 10

What is Yij?

Answer 10

Yij is the value of Y for individual j in group i

Question 11

What is ANOVA for?

Answer 11

a linear model for comparing the means of

more than two groups

Question 12

How does ANOVA work?

Answer 12

by asking if individuals from different groups differ more (on average) than individuals from the same group

Question 13

Null hypothesis ANOVA?

Answer 13

• H0: all group means are equal

Question 14

What is F statistic formula?

Answer 14

F = group mean square/error mean square

MSgroups/MSerror

Question 15

What does large f mean?

Answer 15

the larger the F, the more that group means differ relative to spread within
groups, and the more likely we are to reject the null

Question 16

how do you get F?

Answer 16

1. partition the sums of squares to separate sources of variance in the response
2. calculate the ANOVA table