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Daily high temperature and maximum market price for electric

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The following table shows the daily high temperature and maximum market price for electricity during 7 days this last summer. Using the data in the table calculate the regression equation, including the slope and intercept terms, R squared, and the SE of the regression (SE of the estimate). Based on your results, how well does temperature explain changes in price? How are the two variables mathematically related? How might you use your regression to forecast the price for electricity?
Temp. Prices
70 45
75 48
80 42
85 55
90 63
95 94
100 105

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The solution provides detailed explanations and calculations, including plots in Excel format. It also includes step-by-step instructions for the problem.

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Please see the attached files.

I have used Excel for this purpose. The file is attached.
The regression equation is: y=2.09x - 113.32
where y=price and x=temp.

The slope = 2.09 and the intercept = -113.32
R2=0.815
To calculate the standard error of the estimate, first calculate ...

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