Chapter 12

Question 1

Factorial design

Answer 1

participants are observed across the combination of levels of two or more factors

Ex: factors= gender, attractiveness

Question 2

Between-subjects factorial design

Answer 2

we observe different participants in each group created by combining the levels of at least two factors

1. manipulate the levels of each factor
2. cross the levels of the two factors to create the groups
3. randomly assign different participants to each group

*total of participants= sample size x # of levels for each factor

  10 x 3 x 2 = 60 participants

Question 3

Within-subjects factorial design

Answer 3

we observe the same participants in each group created by combining the levels of at least two factors

1. Manipulate the levels of each factor
2. cross the levels of the two factors to create the groups
3. control for order effects due to observing the same subjects in each group

• total participants = sample size

Question 4

Mixed factorial design

Answer 4

we create groups by crossing the levels of at least one between-subjects factor and one within-subjects factor

1. manipulate the levels of each factor
2. cross the levels of the two factors to create the groups
3. randomly adding different participants to each level
4. Control for order effects due to observing

Question 5

Main effects

Answer 5

A source of variation associated with mean differences across the levels of a single factor

In a table summary, a main effect is a measure if how the row and column means differ across the levels of a single factor

Question 6

Interaction effects

Answer 6

A source of variation associated with how effects of one factor are influenced by, or depend on, the levels of a second factor

In a table summary, an interaction is a measure of how cell means at each level of one factor change across the levels of a second factor

Question 7

Reasons for using factorial designs

Answer 7

To replicate a previous finding and also in the same design demonstrate a new finding

To control for possible threats to validly by adding possible threats as factors in a factorial design

Enhance the informativeness of interpretation because it allows us to analyze the effects of 2 or more factors simultaneously