The data being used for the quiz are based on data that were collected after the
ID: 3364056 • Letter: T
Question
The data being used for the quiz are based on data that were collected after the 2009 war ended that was between Israel and the Hamas militias in the Gaza Strip. Responses were obtained from a group of students whom were exposed to rocket attacks during that period. The variables in the study include:
ID: Used to indicate the ID# of the participant
Age: The age of the individuals that responded to the survey
Gender: The gender of the individuals that responded to the survey
0 = Female
1 = Male
Parents in range; Indicates whether or not the participant’s parents decided to stay in the range of the rockets
0 = Not in range
1 = In range
Anger: Respondents were asked to estimate the level of anger they felt during the war
Fear: Respondents were asked to estimate the level of fear they felt during the war
Perceived Threat: Respondents estimated the likelihood/probability that they would experience risky events within the next 12 months
7.0
Use SPSS to run a Hierarchical Regression Analysis with “age” as the first IV, “anger” as the second IV, and “perceived threat” as the DV.
What is the statistical significance of:
a. Model 1: ______
b. Model 2: ______
ID age gender parents.in.range anger fear perceived.threat 1 35 0 0 4.57.0
64.90 2 40 0 0 7.0 7.0 86.78 3 28 1 0 5.0 5.0 87.97 4 25 1 0 2.0 2.0 44.63 5 26 1 0 5.5 2.0 98.83 6 33 0 1 6.5 2.0 61.45 7 21 1 1 4.0 4.0 42.38 8 29 1 1 5.0 2.5 99.61 9 21 0 1 3.0 3.5 83.61 10 20 1 1 5.5 4.5 76.94 11 39 1 0 6.0 1.5 49.23 12 31 1 1 4.0 2.0 5.16 13 34 0 1 3.0 3.0 64.15 14 34 0 1 4.0 6.0 25.56 15 26 1 0 2.5 5.5 84.39Explanation / Answer
First model
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.18
R Square
0.03
Adjusted R Square
-0.04
Standard Error
28.02
Observations
15
ANOVA
df
SS
MS
F
Significance F
Regression
1
326.98
326.98
0.42
0.53
Residual
13
10207.15
785.17
Total
14
10534.12
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept
87.40
35.40
2.47
0.03
10.92
163.88
age
-0.76
1.18
-0.65
0.53
-3.30
1.78
Second model
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.41
R Square
0.17
Adjusted R Square
0.03
Standard Error
26.98
Observations
15
ANOVA
df
SS
MS
F
Significance F
Regression
2
1800.38
900.19
1.24
0.32
Residual
12
8733.75
727.81
Total
14
10534.12
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept
76.22
34.98
2.18
0.05
0.01
152.43
age
-1.57
1.27
-1.24
0.24
-4.33
1.19
anger
7.78
5.47
1.42
0.18
-4.13
19.68
We can see from the above results that model 1is not statistically significant because F<Significance F. However, model 2 is statistically significant (F>Significance F and hence we reject the null hypothesis of no effect on dependent variable). We can conclude that atleast one variable affects the dependent variable.
In SPSS, run the linear regression as follows: -
1) Click Analyze>Regression>Linear
2) Select Dependent and Independent variable
3) Click ok
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.18
R Square
0.03
Adjusted R Square
-0.04
Standard Error
28.02
Observations
15
ANOVA
df
SS
MS
F
Significance F
Regression
1
326.98
326.98
0.42
0.53
Residual
13
10207.15
785.17
Total
14
10534.12
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept
87.40
35.40
2.47
0.03
10.92
163.88
age
-0.76
1.18
-0.65
0.53
-3.30
1.78
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