A different linear regression model predicts a student's GPA from the number of classes missed, weekly hours spent on studying and their age. The table below gives partial output from SPSS. Unstandardized Std Standardized Coefficients t sig. Coefficients error Constant 0.745 Number of classes missed -0.297 -0.907 Average weekly hours 0.298 0.71 spent studying Student age 0.019 0.03 If a student misses 3 classes, studies 7 hours per week and is 19 years old, what will the model predict as this student's GPA? Give your answer to 3 decimal places.

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A different linear regression model predicts a student's GPA from the number of classes
missed, weekly hours spent on studying and their age. The table below gives partial
output from SPSS.
Unstandardized
Std
Standardized
Coefficients
t sig.
Coefficients
error
Constant
0.745
Number of classes missed -0.297
-0.907
Average weekly hours
0.298
0.71
spent studying
Student age
0.019
0.03
If a student misses 3 classes, studies 7 hours per week and is 19 years old, what will the model
predict as this student's GPA? Give your answer to 3 decimal places.
(Do not be alarmed if you get a negative GPA. The question is asking what the model predicts.
This would mean that the model is not that good. )
Transcribed Image Text:A different linear regression model predicts a student's GPA from the number of classes missed, weekly hours spent on studying and their age. The table below gives partial output from SPSS. Unstandardized Std Standardized Coefficients t sig. Coefficients error Constant 0.745 Number of classes missed -0.297 -0.907 Average weekly hours 0.298 0.71 spent studying Student age 0.019 0.03 If a student misses 3 classes, studies 7 hours per week and is 19 years old, what will the model predict as this student's GPA? Give your answer to 3 decimal places. (Do not be alarmed if you get a negative GPA. The question is asking what the model predicts. This would mean that the model is not that good. )
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