Chapter 9 Flashcards
(27 cards)
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
