4. Experimental Design Iii

Front 1

What does having multiple (more than one) independent variable's allow:

Back 1

A determination of not only the effect of each Independent variable on the dependent variable, but how they interact aswell. E.g. How long it takes to fall asleep with lights on + whether or not there's loud music. Absent = different. loud music = equal.

Front 2

What is a fully crossed experimental design:

Back 2

When you have multiple Independent variables and you collect all combinations of levels data, this leads to a factorial design.

Front 3

What is a factorial design:

Back 3

When each level of one factor (independent variable) is combined with every level of other variable.

E.g. with gender and meal size. we would get

- Small meal: M & F

- Large meal: M & F

Front 4

How do you figure out how many possible conditions are in a factorial design:

E.g. with the meal size & Gender

Back 4

Times the number of levels by each other for each Independent variable.

2x2 factorial design.

2 outcomes for each times each other = 4 possible outcome.

Front 5

In a 2x2 factorial design (4 possible outcomes) where all IV's are between subjects, how would the 40 people be distributed:

Back 5

Small Large

Male 10 10

Female 10 10

Front 6

In a 2x2 factorial design where all IV's are within-subjects, how would the 40 people be distributed amongst the 4 outcomes:

Back 6

Large Small

Male 40 40

Female 40 40

Front 7

In a 2x2 factorial design where one IV is within subjects and one IV is between subjects (mixed design), what would distribution of the 40 look like and explain:

Back 7

Large Small

Male 20 20

Female 20 20

As, each participants receives each level of the within-subjects IV and one level of the between subjects IV.

Front 8

With factorial designs you can get two types of effects, what are they:

Back 8

Main effects = The effects of one IV on the DV, ignoring the other IV's.

Interaction effects = The effects of one IV on the DV taking into account the other IV's in the study.

Front 9

What are main effects and interaction effects:

Back 9

Main effects: The effects of one IV on the DV, ignoring other IV's.

There's a main effect for every IV.

Interaction effect: The effects of one IV on the DV, taking into account the other IV's in the study. There's an interaction for every combination of IV's.

Front 10

What should be interpreted first between main effects and interaction effects:

Back 10

Interaction effects before main effects.

Front 11

When looking at graphs showing data for an experiment like the gender with food and appearance, what 2 types of line styles would we expect to see for an interaction:

Back 11

Converging and diverging:

Front 12

How would you know if there is no interaction:

Back 12

If the lines are parallel.

Front 13

How many sources of variability are there in a 2-factor experiment:

Back 13

3 sources of variability.

2 main effects (1 for each IV)

1 interaction effect.

Front 14

What is the relationship between between interaction and main effects:

Back 14

They arnt really dependent on each other in anyway.

Front 15

Can you determine if the observed effects are statistically significant, and why:

Back 15

No not really, you need to do statistical tests to just see if they are statistically different.