1. High-Low; Analysis of Regression Results Regression analysis is commonly used to estimate costs. However, the usefulness of the results depends upon the quality of the data. Fletcher Inc. is a local delivery company. The employees handle deliveries for a variety of companies that have developed apps that allow customers to place orders for food, beverages, packages, etc. The controller of Fletcher would like to come up with an estimate of the cost behavior for the delivery costs. Fifteen months of data were collected, and the data appear below. Using the high-low method, the controller did a quick calculation and estimated the variable and fixed portions of the delivery costs. A new employee in the accounting department, however, suggested that regression would give a much better estimate of the costs.

Observation	Delivery Costs	Number of Deliveries
1	$148,620	11,540
2	150,980	12,180
3	199,200	16,560
4	143,100	11,685
5	203,695	16,685
6	183,065	14,875
7	156,390	13,010
8	193,440	13,010
9	189,330	15,555
10	151,200	11,970
11	158,445	12,630
12	188,085	15,300
13	182,320	14,580
14	144,520	11,980
15	155,680	13,000

Required

1. Using the given data, determine the estimated cost equation for delivery costs using the high-low method.
2. Using the data available, determine the estimated cost equation for the delivery costs using regression.
3. Graph the data to determine if any adjustments should be made to the regression analysis done in requirement 2.
4. Recompute the estimated cost equation for the delivery costs after making any adjustments to the data as a result of your analysis in requirement 3. What can you conclude about the various cost equations?