Psychology 2080A/B Chapter Notes - Chapter 12: Factorial Experiment

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Published on 22 Apr 2013
School
Western University
Department
Psychology
Course
Psychology 2080A/B
CHAPTER 12: TRUE EXPERIMENTS, PART 2: FACTORIAL DESIGNS
-often we want to examine the effect of two or more variables in a single
experiment because of :
-efficiency: as long as you are designing an experiment, building
another independent variable into the design may not require much
additional effort
factorial design: research design that involves all combinations of at least
two variables of two or more independent variables
-in the simplest case we have a 2 x 2 factorial
-you can have as many levels but increasing complexity will require more
time to conduct the experiment
Main Effects
main effect: in a factorial experiment the effect of one independent variable
average over all levels of another independent variable
interaction: when the effect of one independent variable depends on the
level of another independent variable
-if graphical representation of a factorial experiment shows curves aren’t
parallel there is an interaction between the variables
-to have interaction if one or the other independent variable has no main
effect or even if neither independent variable has a main effect
Types of Interactions
antagonistic interactions: interaction in which the two independent variables
tend to reverse each others effects
synergistic interaction: interaction in which the two independent variables
reinforce each others effects
ceiling-effect interaction: interaction in which one variable has a smaller
effect when paired with higher levels of a second variable
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Document Summary

Chapter 12: true experiments, part 2: factorial designs. Often we want to examine the effect of two or more variables in a single experiment because of : In the simplest case we have a 2 x 2 factorial. You can have as many levels but increasing complexity will require more time to conduct the experiment. Main effects main effect: in a factorial experiment the effect of one independent variable average over all levels of another independent variable interaction: when the effect of one independent variable depends on the level of another independent variable. If graphical representation of a factorial experiment shows curves aren t parallel there is an interaction between the variables. To have interaction if one or the other independent variable has no main effect or even if neither independent variable has a main effect.

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