Week 7 Flashcards

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1
Q

What is a statistical model?

A

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

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2
Q

What is εi?

A

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

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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

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4
Q

What is a generalised linear model?

A

a linear model that assumes a non-normal distribution

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5
Q

What is a plain linear model?

A

is a
linear model that assumes a
normal distribution

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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

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7
Q

What is µ?

A

is the overall mean

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8
Q

What is Ai?

A

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

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9
Q

what are residuals?

A

errors are often called residuals

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10
Q

What is Yij?

A

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

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11
Q

What is ANOVA for?

A

a linear model for comparing the means of

more than two groups

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12
Q

How does ANOVA work?

A

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

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13
Q

Null hypothesis ANOVA?

A

• H0: all group means are equal

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14
Q

What is F statistic formula?

A

F = group mean square/error mean square

MSgroups/MSerror

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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

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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