Lecture 3 - Repeated measures design and assumptions

Question 1

(lecture):

What’s the main advantage of using a within-subjects design? (over a between-subjects design)

Answer 1

(lecture):

Allows us to estimate the individual differences and remove it from the error term. So the error term is therefore smaller.

More sensitive to treatment effects.

More economical - need less participants (because each participant is part of all experimental conditions).

Question 2

(lecture):

How do you calculate the F ratio?

Answer 2

(lecture):

F = Between-groups variation (treatment effects + experimental error) / Within-groups variation (experimental error)

Question 3

(lecture):

Transformed matrix

Answer 3

(lecture):

Not interested in the individual differences, we’re interested in how the condition affected each persons results.

So instead of someone having higher scores than another person, we see for each individual person how much their scores differed between conditions.

(the lecture explains this really well)

Question 4

(lecture):

What are 2 within-subjects assumptions?

Answer 4

(lecture):

• Normality
• Sphericity

Question 5

(lecture):

Describe what sphericity means.

Answer 5

(lecture) :
1. The core relations between the conditions are similar.
2. The variances of differences between all conditions are the same.

(research what it means, she does explain it in the lecture but I zoned out)