ANOVA

Question 1

When do we use ANOVA?

Answer 1

ANOVA is technique used when all the explanatory variables are categorical.

Question 2

When do we do one-way ANOVA?

Answer 2

When we have one categorical variable

Question 3

When do we do a two-way ANOVA?

Answer 3

If there are two or more factors then we use two or three-way analysis of variance.

Question 4

Which mean squares do we use for the F-test?

Answer 4

Within group and between group

Question 5

What are the assumptions about the variances and the populations for two-way ANOVA?

Answer 5

• The samples are independent
• The variances of the populations are equal
• The groups have the same sample size
• The populations are normally or approximately normally distributed

Question 6

How many null hypotheses (and how many F-tests) do we have in a two-way anova?

Answer 6

3

Question 7

What is the outcome in a Logistic Regression?

Answer 7

Binary (yes/no or 0/1)

Question 8

Which link function do we use for a logistic regression?

Answer 8

logit(p)=log(p)/log(1-p)

Question 9

What is the outcome in a Poisson regression?

Answer 9

Non-negative integer

Question 10

Which link function do we use for a poisson regression?

Answer 10

log

Question 11

ANOVA

Analysis of variance uses the

Answer 11

the ratio of two sources of variability to test the null hypothesis
•Between group variability estimates both experimental error and treatment effects
•Within subjects variability estimates experimental error
•The assumptions that underly this technique directly follow on from the F-ratio.

Question 12

when do we use Analysis of Variance (ANOVA)

Answer 12

is a technique used when all the explanatory variables are categorical.

Question 13

what is the aim of ANOVA

Answer 13

to compare two or more means, by comparing the variances

Question 14

what is a non-parametric method equivalent to one-way ANOVA.

Answer 14

the Kruskal-Wallis

Question 15

what assumptions are made in one-way ANOVA

Answer 15

Each group or level has more than 30 elements. If this is violated, we need to be cautious
with the interpretation. As with linear models, we also assume that the residuals are normally distributed.

Question 16

what are the null and alternative hypotheses in one-way ANOVA

Answer 16

H0 : all μ’s for each level are equal, i.e. μ1 = μ2 = . . . = μK
H1 : at least one μ differs
Where μ is the mean

Question 17

Df Sum Sq Mean Sq F value Pr(>F)
drug 2 28.22 14.111 11.91 0.000256 ***

Residuals 24 28.44 1.185

Signif. codes: 0 ’’ 0.001 ’’ 0.01 ’’ 0.05 ’.’ 0.1 ’ ’ 1

interpret this r output

Answer 17

p-value is smaller than 0.05, thus we can reject the null hypothesis

Question 18

name a plot for interpreting One-Way ANOVA

Answer 18

Box-and-whisker plots are particularly suitable for interpreting differences between data pertaining to different levels of the same factor

Question 19

why it is called two-way analysis of variance.

Answer 19

we have two independent variables.

Question 20

assumptions of two-way ANOVA

Answer 20

1. The samples are independent
2. The variances of the populations are equal
3. The populations must have the same sample size
4. The populations are normally or approximately normally distributed

Question 21

two-way ANOVA, we are performing three different F tests with the following null and alternative
hypotheses.

Answer 21

H0 :
1. There is no difference in the means of the first factor
2. There is no difference in the means of the second factor
3. There is no interaction between the two factors (they are independent)

H1 :
1. There is a difference in the means of the first factor
2. There is a difference in the means of the second factor
3. There is an interaction between the two factors (they are not independent