Multiple R 0.969886 R square 0.940677 Adjusted R square 0.920903 Standard error
ID: 3179272 • Letter: M
Question
Multiple R
0.969886
R square
0.940677
Adjusted R square
0.920903
Standard error
0.850311
Observations
13
df
SS
MS
F
Significance F
Regression
3
103.1851
34.39502
47.57077
7.61146E-06
Residual
9
6.507255
0.723028
Total
12
109.6923
Coefficients
Standard Error
t-stat
P-vaue
Intercept
87.89042
3.445413
25.5094
1.05E-09
X1
0.33874
0.083166
-3.07957
0.13149
X2
-4.63321
0.730602
-3.71436
0.00481
X3
1.00673
0.013532
5.217815
0.00055
Use the following output from a regression analysis to answer questions 1-5
1. At an alpha level of 0.05, we can conclude that:
a. All variables are significant
b. Only variable X1 is significant
c. Only variables X2 and X3 are significant
d. No variables are significant
2. The “slopes” of the variables are:
a. -0.25612, -2.71372, and 0.070606
b. 0.083166, 0.730602, and 0.013532
c. 0.33874, -4.63321, 1.00673
d. Slopes cannot be determined by the information given.
3. Multicollinearity likely exists between variables:
a. X1 and X3
b. X2 and X3
c. X2 and X1
d. It cannot be determined from the information given
4. The output shows that:
a. The overall model is significant at an alpha level of 0.05
b. 68% of the residuals are within ± 0.850311
c. The correlation for this model is 0.969885
d. All of the above statements are true
5. A general observation about this model is that:
a. The sample size is 24
b. Too many variables are included
c. All variables are indicator variables
d. Overall, the model is significant
Multiple R
0.969886
R square
0.940677
Adjusted R square
0.920903
Standard error
0.850311
Observations
13
Explanation / Answer
1. p-value corresponding to X1 = 0.13149
Which is greater than 0.05 wo X1 is not significant.
So correct option is c. Only variables X2 and X3 are significant.
2. Slopes are c. 0.33874, -4.63321, 1.00673
3. Multicollinearity we can't defined using given data.
So the correct option is d. It cannot be determined from the information given.
4. d. All of the above statements are true
F = 47.57
Fc = 0.0000076
So F > Fc so the overall model is significant at an alpha level of 0.05.
68% of the residuals are within ± 0.850311
The correlation for this model is Multiple R = 0.969885
Because by using table we can say all statements are true.
5. A general observation about this model is that:
d. Overall, the model is significant
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