Use the Stat_Grades data set to determine the relationships between a student’sshort-form IQ score,previous GPA, and the student’sFinal Examination points.
a. What are the correlations for each pair of variables? You may use a correlation matrix to show this if you like.
b. What would be the predictedFinal Examination points for a student who has anIQ score of 120 and had a 3.35 GPA using multiple regression?
|
Descriptive Statistics |
|||
|
Short Form IQ Test Score |
115.34 |
9.967 |
105 |
|
2.7789 |
.76380 |
105 |
|
|
Correlations |
|||
|
Short Form IQ Test Score |
Previous GPA |
||
|
Short Form IQ Test Score |
Pearson Correlation |
1 |
.570** |
|
Sig. (2-tailed) |
.000 |
||
|
N |
105 |
105 |
|
|
Previous GPA |
Pearson Correlation |
.570** |
1 |
|
Sig. (2-tailed) |
.000 |
||
|
N |
105 |
105 |
|
|
**. Correlation is significant at the 0.01 level (2-tailed). |
|||
|
Descriptive Statistics |
|||
|
Mean |
Std. Deviation |
N |
|
|
Short Form IQ Test Score |
115.34 |
9.967 |
105 |
|
Final Exam Points |
61.48 |
7.943 |
105 |
|
Correlations |
|||
|
Short Form IQ Test Score |
Final Exam Points |
||
|
Short Form IQ Test Score |
Pearson Correlation |
1 |
.363** |
|
Sig. (2-tailed) |
.000 |
||
|
N |
105 |
105 |
|
|
Final Exam Points |
Pearson Correlation |
.363** |
1 |
|
Sig. (2-tailed) |
.000 |
||
|
N |
105 |
105 |
|
|
**. Correlation is significant at the 0.01 level (2-tailed). |
|||
|
Descriptive Statistics |
|||
|
Mean |
Std. Deviation |
N |
|
|
Final Exam Points |
61.48 |
7.943 |
105 |
|
Previous GPA |
2.7789 |
.76380 |
105 |
|
Correlations |
|||
|
Final Exam Points |
Previous GPA |
||
|
Final Exam Points |
Pearson Correlation |
1 |
.498** |
|
Sig. (2-tailed) |
.000 |
||
|
N |
105 |
105 |
|
|
Previous GPA |
Pearson Correlation |
.498** |
1 |
|
Sig. (2-tailed) |
.000 |
||
|
N |
105 |
105 |
|
|
**. Correlation is significant at the 0.01 level (2-tailed). |
|||
|
Variables Entered/Removeda |
|||
|
Model |
Variables Entered |
Variables Removed |
Method |
|
1 |
Previous GPA, Short Form IQ Test Scoreb |
. |
Enter |
|
a. Dependent Variable: Final Exam Points |
|||
|
b. All requested variables entered. |
|||
|
Model Summary |
||||
|
Model |
R |
R Square |
Adjusted R Square |
Std. Error of the Estimate |
|
1 |
.507a |
.257 |
.243 |
6.912 |
|
a. Predictors: (Constant), Previous GPA, Short Form IQ Test Score |
||||
|
ANOVAa |
||||||
|
Model |
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
|
1 |
Regression |
1688.794 |
2 |
844.397 |
17.673 |
.000b |
|
Residual |
4873.396 |
102 |
47.778 |
|||
|
Total |
6562.190 |
104 |
||||
|
a. Dependent Variable: Final Exam Points |
||||||
|
b. Predictors: (Constant), Previous GPA, Short Form IQ Test Score |
||||||
|
Coefficientsa |
||||||||
|
Model |
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
95.0% Confidence Interval for B |
|||
|
B |
Std. Error |
Beta |
Lower Bound |
Upper Bound |
||||
|
1 |
(Constant) |
38.231 |
8.241 |
4.639 |
.000 |
21.884 |
54.578 |
|
|
Short Form IQ Test Score |
.093 |
.083 |
.117 |
1.130 |
.261 |
-.071 |
.258 |
|
|
Previous GPA |
4.485 |
1.080 |
.431 |
4.153 |
.000 |
2.343 |
6.626 |
|
|
a. Dependent Variable: Final Exam Points |
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