Chapter 9 Flashcards
A description of how many variables are being used in the independent and the dependant
factoral design
2 x 4 factorial design has how many conditions?
8, first independent variable has 2 levels and the second independent variable has 4 levels
The number of variations of an independent variable
level
two temperature levels, four humidity levels and three noise levels has how many conditions?
24
Refers to individual cells in a factorial design and the levels of independent variables
condition
A factorial design that uses the same participants for each condition
within-subject design
a factorial design that uses different participants for each condition
between-subject design
A factorial design that includes at least one between-subject variable and one within-subject variable
mixed-factorial design
Why use factorial designs?
- Examine the effect of multiple variables at once
- In real life multiple variables interact together
- Examining interactions between independent variables
- finding moderator variables
- efficient
- cheeper
The independent variable that has an overall effect on a dependant variable
main effect
When the independent variable influences a dependant variable differs depending on another independent variable
interaction effect
A variable that alters the strength or direction of a correlation
moderator variable
Limitations of factorial designs
- the total number of conditions might be too large to control
- Takes longer to conduct
A representative statistic for the average
cell mean
Analysis for dependant variables on an interval or ratio scale
ANOVA, analysis of variance
The effect of one independent variable at a particular level of another independent variable
simple main effect
tests that are conducted after initial findings
post-hoc tests
Order of tests conducted
ANOVA - test of simple main effects - post-hoc comparisons
variables that are characteristics of the participants
subject variables
How a participant reacts depending on the situation
situational factor
An experimental design that uses one subject variable and one situational variable
person x situation factorial design
quasi-independent variables
variables that cannot be manipulated but can distinguish different groups
When two independent effect each other which influences the dependent variable
two-way interactions
when two independent variables in fluence a third
three-way interaction
Testing every possible order for each level
Complete counter balancing
When each treatment condition will come in every possible order
latin square
When each sequence comes only once, but requires an even number of levels
balanced latin sequence
