What Type of Anova Testing should be used to answer the following questions? In
ID: 3227193 • Letter: W
Question
What Type of Anova Testing should be used to answer the following questions?
In order to investigate the effectiveness of a new kind of therapy using virtual reality on various phobias, Dr. Chang collected data from individuals with two common types of phobias (Fear of Flying and Fear of Outsiders). Dr. Chang recorded the Gender of each individual, coded as 1 = “female” and 2 = “male, and their Type of Phobia, 1 = Fear of Flying and 2 = Fear of Outsiders. He believes that virtual reality therapy (VRT) will improve outcomes for his patients, and he tested them at three time points: Before VRT, Immediately after VRT, and 1 month after VRT. Dr. Chang measured the extent to which they experienced symptoms of their phobia at each time point on a scale of 1 = “not at all” to 10 = “constantly”. Dr. Chang also manipulated Therapy Frequency, randomly assigning participants to attend once, twice, or three times per week. The data from his study is provided below:
Participant
Gender
Type of Phobia
Therapy Frequency
Before VRT
Immediately after VRT
1 month after VRT
Hugo
2
1
1
8
7
5
Jack
2
1
2
9
9
6
Kate
1
1
3
5
6
4
John
2
1
1
9
10
7
Claire
1
1
2
7
6
3
Charlie
2
1
3
4
3
1
Ben
2
2
1
8
6
2
Juliet
1
2
2
2
2
5
Richard
2
2
3
10
10
5
Ethan
2
2
1
5
6
2
Alex
1
2
2
9
7
6
Tom
2
2
3
7
7
5
What Type of Anova Testing should be used to answer the following questions?
1. Is there a difference in phobia symptoms 1 month after VRT based on how often they attended therapy (Therapy Frequency)?
2. Do phobia symptoms change over time for all participants?
3. Is there a relationship between phobia symptoms Immediately after VRT and phobia symptoms 1 month after VRT?
Participant
Gender
Type of Phobia
Therapy Frequency
Before VRT
Immediately after VRT
1 month after VRT
Hugo
2
1
1
8
7
5
Jack
2
1
2
9
9
6
Kate
1
1
3
5
6
4
John
2
1
1
9
10
7
Claire
1
1
2
7
6
3
Charlie
2
1
3
4
3
1
Ben
2
2
1
8
6
2
Juliet
1
2
2
2
2
5
Richard
2
2
3
10
10
5
Ethan
2
2
1
5
6
2
Alex
1
2
2
9
7
6
Tom
2
2
3
7
7
5
Explanation / Answer
formula for correaltion:
corr r=cov/(sd of x * sd of y)
cov= E[XY] - E[X]*E[Y]
t-stat= r*sqrt(n-2)/sqrt(1-r^2)
correlation= 0.586992 coefficient of determination=correlation^2 0.344559 we use t-test for testing if this correlation is significant H0: correlation is not significant Ha: correlation is significant t-stat= 2.292845 p-value= 0.021282 p-value<.05; reject H0; conclude yes, this correlation is significantRelated Questions
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