Scenario: Data was recorded of the number of hours middle school students watche

Question

Scenario: Data was recorded of the number of hours middle school students watched TV before the final exam and their scores on the final exam - see the first 2 columns below Xand ). The results of the Regression output (using MS Excel is shown on the right hand side under "SUMMARY OUTPUT SCORE ON EXAMOUT OF 100 (Y) WATCHING TV SUMMARY OUTPUT MultipleR R Square Adjusted R Square Standard Error 0.985746614 3.705652783 15 70 ANOVA MS 1 8435.776474 8485.770474 617.9625265 2.19002E-15 18 247.1735259 13.73186255 95 50 Total 873295 15 cients Stundard Error t Stot r 95% Lower 95 0% 95.0% 1.807912284 56.1389759 1.1424-21 97.69G0614 105 2926269 97.6960614 105.2926269 3.195547533 0128547671 -24.85885208 2.19002E-15-3.465616168 -2.92547888-3.465616168-2.925478898 Ute Lower 95% HOURS WATCHING TV 98 Per the above regression model, for every 10 additional hours a student studies, the GPA can improve by 1.00 0.68 0.52 0.25

Explanation / Answer

Regression coefficients represent the mean change in the response variable for one unit of change in the predictor variable keeping other predictor variables constant.

Here Hours spent watching tv is the predictor variable

And the score out of 100 is the response variable.

Here the coefficient for hours watching tv is -3.1955 indicates that for every 1 hour spent in watching tv might reduce the score by 3.195.

So every 1 additional hour spent on studying instead of watching tv results in 3.195 increase in score.

Hence for every 10 additional hours of studies, 31.95 increase will be shown in the score which in turn increase GPA by 1.00 point.

Answer:1.00

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