Question

onth	Number of Pancakes	Total Operating Costs
July . . . . . . . . . . . .	3,700	$2,320
August . . . . . . . . . .	4,000	$2,460
September . . . . . . .	3,000	$2,370
October . . . . . . . . .	3,300	$2,270
November . . . . . . .	3,800	$2,570
December . . . . . . .	3,500	$2,540

Evan​'s Golden HotGolden Hot Pancake Restaurant features sourdough pancakes made from a strain of sourdough dating back to the Yukon gold rush. To plan for the​ future, Evan needs to figure out his cost behaviour patterns. He has the following information about his operating costs and the number of pancakes​ served:

Requirements: Use Microsoft Excel to run a regression analysis on

Evan​'s monthly​ data, then do the following calculations.

1.	Based on the output from the Excel​ regression, determine Evan​'s monthly operating cost equation.
2.	Based on the​ R-square shown on the regression​ output, how well does this cost equation fit the​ data?

Requirement 1. Based on the output from the Excel​ regression, determine Evan​'s monthly operating cost equation.

​(Round the amounts to the nearest​ cent.)

y​ =​$( ) x ​+​$( )

Requirement 2. Based on the​ R-square shown on the regression​ output, how well does this cost equation fit the​ data?

The​ R-square is ....... . This indicates that the regression line and cost equation ......does not fit the data at all. fits the data quite well. should be used with caution. The data ............................will not may or may not should do a good job of predicting future monthly operating costs within the same relevant range.

Answer 1

Answer 1
operating cost equation. = 0.1519x + 1882.4
Fixed cost	$ 1,882.40
variable cost per Pancakes	$     0.1519
Answer 2
R2 is concern with how close the data are to the fitted regression line. In simple wors, it is represent predication power of regression equation for farcating purpose. Techanically it is called coefficient of determination.
The data will not may or may not should do a good job of predicting future monthly operating costs within the same relevant range because R2 is to much less.