Question

HELP ME PLEASE! HALF-DONE ANSWERS WILL BE DELETED! 15 POINTS!

Answer 1

Answer:

G: The residual plot given displays the linear model from the regression calculator as being a good model for it represets the points and how the linear model compared to the residual model calculates to a similar, if not same result.

Based on the equation we did for 2d:

$\frac{predicted value}{measured value} = residual$

$9.2-2.23=6.97\\19.5-3.77=15.73\\15.5-3.92=11.58\\0.7-1.11=-1.04\\21.9-3.60=18.3\\13.8-1.42=12.38$

H: We can interpret the average or close accurate of a student that studies for 15 hours a week to be around 3.92 based on previous findings. Along with that, the scatterplot should be different by the first set of differences that was subtracted.

When plotting the new points, be sure to make them a seperate color of shape (depending on how creative you wish to be) so you can tell the two apart form one another.

Hope this Helps!

Answer 2

Answer:

G) Yes, because the plots and the linear model both align to produce a similar calculated sum.

H) I need to see the data table again for step 2d.

Step-by-step explanation:

1.) You scatter plot should be off by 6.97, since that was the first difference in your data table set of terms.

Basically subtract all of the GPAs from the Hours in the table.

Ex). Hours - GPA = Difference

or like before,

      9.2 - 2.23 = 6.97

Do the rest of the numbers like this then plot the answers.  I'd advise you plot your second set of scatter plot points in a different color.