PSYC 210- Factorial ANOVA Exam Questions with CORRECT Answers (Grade A+)
Question 1:
Factorial ANOVA
Answer:
An Analysis of Variance used when there are two or more independent variables. When there are two,
the ANOVA is called a Two-Way ANOVA, three independent variables would use a Three-Way ANOVA,
etc. (Def. from allpsych.com)
Question 2:
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
Question 3:
main effect
Answer:
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)
Question 4:
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?
Answer:
[Question text not safely extractable from source.]
Question 5:
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
Answer:
interactions
Question 6:
No interaction effect
Answer:
no post hoc test
Question 7:
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
Question 8:
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)
Question 9:
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
Answer:
c. We want to see whether type of mattress and type of pillow influence quality of sleep Explanation
The only example with 2 or more predictor variables that are both nominal and one outcome is the
third answer here.
Question 10:
Question 1:
Factorial ANOVA
Answer:
An Analysis of Variance used when there are two or more independent variables. When there are two,
the ANOVA is called a Two-Way ANOVA, three independent variables would use a Three-Way ANOVA,
etc. (Def. from allpsych.com)
Question 2:
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
Question 3:
main effect
Answer:
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)
Question 4:
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?
Answer:
[Question text not safely extractable from source.]
Question 5:
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
Answer:
interactions
Question 6:
No interaction effect
Answer:
no post hoc test
Question 7:
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
Question 8:
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)
Question 9:
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
Answer:
c. We want to see whether type of mattress and type of pillow influence quality of sleep Explanation
The only example with 2 or more predictor variables that are both nominal and one outcome is the
third answer here.
Question 10:
