Chapter 11: Factorial Designs Flashcards
Why do researchers design experiments that include more than one independent variable?
because it creates a more REALISTIC situation compared to a single factor design because behavior is usually influenced by a variety of different variables acting and interacting simultaneously.
factors
when two ore more independent variables are examined in one study
levels
number of conditions for each factor
factorial design
a research study involving two or more factors (IVs).
Describe an example of a factorial design that uses quasi independent variables.
a factorial design that invovles variables such as age or gender that are not manipulated are called quasi-independent variable factorial designs.
ex/ studying how new video game violence (factor A) and gender (B) are related to aggressive behavior (dependent variable). The gender is a quasi-independent variable because it cannot be manipulated.
What kind of factorial design is 2 x 3? How many conditions are there?
this is a 2-factorial design in which there are 2 independent variables with three levels each. There are 6 conditions in this type of factorial design
example of a 2 x 2 factorial design
ex/ schizophrenic and control group, who experience placebo or drug treatment. You get four scenarios.
schizophrenic and placebo
schizophrenic andd drug
normal and placebo
normal and drug.
What is a main effect
seeing how each individual factor (IV) influences behavior/measure (DV). MEAN DIFFERENCES among the levels of one factor. ex/ differences between the row means define the main effect for the row factor.
the main effects reflect results obtained if each factor was examined on its own.
What is an interaction
seeing how the group of factors (both IV’s) act together.
if factors work independently, then there is ___ interaction (yes or no)
no interaction.
in terms of main effects, how can you tell if there is an interaction between the two independent variables?
if the main effects of one factors doesn’t apply EQUALLY across the mean conditions of the 2nd factor.
when graphing results, non parallel lines between factors indicates an ____, meaning that the factors are ____
when graphing results, non parallel lines between factors indicates an INTERACTION, meaning that the factors are DEPENDENT ON ONE ANOTHER.
A gap in the graph indicates
that there is a main efffect in the y variable
a slope in the graph indicates:
that there is a main effect in the x variable.
if the two variable lines in the graph intersect right at the mid point, does this mean there is a main effect in the x axis?
NO! the two slopes cancel each other out. There is actually no change in means.