Week 7 Flashcards

1
Q

What is a statistical model?

A

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

2
Q

What is εi?

A

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

3
Q

Why are linear models the go-to in biology?

A

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

4
Q

What is a generalised linear model?

A

a linear model that assumes a non-normal distribution

5
Q

What is a plain linear model?

A

is a
linear model that assumes a
normal distribution

6
Q

What are numerical responses assumed to have?

A

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

7
Q

What is µ?

A

is the overall mean

8
Q

What is Ai?

A

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

9
Q

what are residuals?

A

errors are often called residuals

10
Q

What is Yij?

A

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

11
Q

What is ANOVA for?

A

a linear model for comparing the means of

more than two groups

12
Q

How does ANOVA work?

A

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

13
Q

Null hypothesis ANOVA?

A

• H0: all group means are equal

14
Q

What is F statistic formula?

A

F = group mean square/error mean square

MSgroups/MSerror

15
Q

What does large f mean?

A

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

16
Q

how do you get F?

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