PSYC 210 EXAM COMPREHENSIVE QUESTIONS
AND ANSWERS GRADED A+
◉ what's the simplest versions of factorial anova?
Answer: between subject, 2 levels
ex. people's ratings of food type if food is hot or cold
food item and food temp
◉ main effect
Answer: In a factorial design, the overall effect of one independent
variable on the dependent variable, averaging over the levels of the
other independent variable.
observed effects of each factor by themselves
Each factor will be associated with a certain amount of variance in
scores, not taking into account the other factor(s)
An effect called main effect only if it is significant (there is no
observed effect)
Ex.
,main effect for food temp → do ppl like hot food more than cold?
Main effect food item → do ppl like ice cream more than pancakes?
◉ interactions
Answer: key reason to use factorial ANOVA
Does the effect of predictor variable 1 on the outcome change based
on level of predictor 2
Ex. do ppl's ratings of food items change based on food temperature?
If it does change, the effect of how much you look the food item
changes based on the food temperatures
ex. hot ice cream, hot pancake, cold ice cream, cold pancake
◉ No interaction effect
Answer: no post hoc test
◉ Adv and Disadv of Between subject and Within subject factorial
Answer: between -sbuject one group answers all questions/ does al
ltests
Could be bias
Less ppl
, Within subject- 5 ppl for this, 5ppl for that
Requires much more ppl
Less bias
◉ factorial anova hypothesis
Answer: Hypothesis
Null mean are the same (main effect)/ mean are the same
(interactions)
Alt. the means are not all the same (interactions)
◉ Which of these scenarios is a good candidate for a factorial
ANOVA?
a. We want to see if age and height affect weight
b. We want to see if amount of light affects how high plants grow
c. We want to see whether type of mattress and type of pillow
influence quality of sleep
d. We want to see if chapstick sales are affected by flavor of
chapstick
Answer: c. We want to see whether type of mattress and type of
pillow influence quality of sleep
AND ANSWERS GRADED A+
◉ what's the simplest versions of factorial anova?
Answer: between subject, 2 levels
ex. people's ratings of food type if food is hot or cold
food item and food temp
◉ main effect
Answer: In a factorial design, the overall effect of one independent
variable on the dependent variable, averaging over the levels of the
other independent variable.
observed effects of each factor by themselves
Each factor will be associated with a certain amount of variance in
scores, not taking into account the other factor(s)
An effect called main effect only if it is significant (there is no
observed effect)
Ex.
,main effect for food temp → do ppl like hot food more than cold?
Main effect food item → do ppl like ice cream more than pancakes?
◉ interactions
Answer: key reason to use factorial ANOVA
Does the effect of predictor variable 1 on the outcome change based
on level of predictor 2
Ex. do ppl's ratings of food items change based on food temperature?
If it does change, the effect of how much you look the food item
changes based on the food temperatures
ex. hot ice cream, hot pancake, cold ice cream, cold pancake
◉ No interaction effect
Answer: no post hoc test
◉ Adv and Disadv of Between subject and Within subject factorial
Answer: between -sbuject one group answers all questions/ does al
ltests
Could be bias
Less ppl
, Within subject- 5 ppl for this, 5ppl for that
Requires much more ppl
Less bias
◉ factorial anova hypothesis
Answer: Hypothesis
Null mean are the same (main effect)/ mean are the same
(interactions)
Alt. the means are not all the same (interactions)
◉ Which of these scenarios is a good candidate for a factorial
ANOVA?
a. We want to see if age and height affect weight
b. We want to see if amount of light affects how high plants grow
c. We want to see whether type of mattress and type of pillow
influence quality of sleep
d. We want to see if chapstick sales are affected by flavor of
chapstick
Answer: c. We want to see whether type of mattress and type of
pillow influence quality of sleep
