Question

Lackland

Lackland Ski Resort uses multiple regression to forecast ski lift revenues for the next week based on the forecasted number of days with temperatures above 10 degrees and predicted number of inches of snow. The following function has been developed:

Sales = 10,902 255 (number days predicted above 10 degrees) 300 (number of inches of snow predicted)

Other information generated from the analysis include

Adjusted R2 = 0.6789

Standard Error of the Estimate (SEE) = 1,879

F-statistic = 6.279 with a significance of 0.049

Which of the following represents an accurate interpretation of the results of Lackland’s regression analysis?

rev: 09_28_2018_QC_CS-139975, 11_05_2018_QC_CS-146424

Multiple Choice

• The predicted number of days above 10 degrees is a more significant variable than the number of inches of snow.

• The relationships are not significant.

• 67.89% of the variation in revenue is explained by the predicted number of days above 10 degrees and the number of inches of snow.

• 6.729% of the variation in revenue is explained by the predicted number of days above 10 degrees and the number of inches of snow.

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Answer 1

Since adjusted R square= 0.6789 which can be interpreted as 67.89% of the variation in revenue is explained by the predicted number of days above 10 degrees and the number of inches of snow.

So according to given question which given option is accurate interpretation so answer is 67.89% of the variation in revenue is explained by the predicted number of days above 10 degrees and the number of inches of snow.

Since Option A CAN NOT BE BECAUSE IT IS COMPARING

OPTION B IS STATING THAT IT IS NOT SIGNIFICANT WHICH IS FALSE BECAUSE P VALUE SMALLER THAN 0.05

OPTION D IS WRONG BECAUSE F=6.729 WHICH IS TEST STATISTIC.