Caiman Distribution Partners is the Brazilian distribution company of a U.S. consumer products firm. Inflation in Brazil has made bidding and budgeting difficult for marketing managers trying to penetrate some of the country's rural regions. The company expects to distribute 450,000 cases of products in Brazil next month. The controller has classified operating costs (excluding costs of the distributed product) as follows:

Account	Operating Cost			Behavior
Supplies	$	350,000		All variable
Supervision		210,000		$	140,000	Fixed
Truck expense		1,200,000		$	180,000	Fixed
Building leases		845,000		$	540,000	Fixed
Utilities		210,000		$	115,000	Fixed
Warehouse labor		850,000		$	140,000	Fixed
Equipment leases		750,000		$	600,000	Fixed
Data processing equipment		955,000		All fixed
Other		860,000		$	410,000	Fixed
Total	$	6,230,000

Although overhead costs were related to revenues throughout the company, the experience in Brazil suggested to the managers that they should incorporate information from a published index of Brazilian prices in the distribution sector to forecast overhead in a manner more likely to capture the economics of the business.

Following instructions from the corporate offices, the controller's office in Brazil collected the following information for monthly operations from last year:

Month	Cases	Price Index	Operating Costs
1	352,000	117	$5,769,139
2	369,000	119	5,876,638
3	365,000	120	5,919,905
4	387,000	124	5,997,617
5	381,000	126	6,009,135
6	402,000	127	6,113,364
7	374,000	130	5,988,495
8	419,000	135	6,203,868
9	405,000	135	6,196,130
10	428,000	134	6,256,625
11	424,000	138	6,278,799
12	439,000	141	6,432,255

These data are considered representative for both past and future operations in Brazil.

b. Use the high-low method to compute an estimate of operating costs assuming that 450,000 cases will be shipped next month. (Round variable cost per unit to 2 decimal places and other intermediate calculations to nearest whole number.)

c-1. Enter the regression coefficients. (Round "Cases" to 2 decimal places.)

c-2. Compute an estimate of operating costs assuming that 450,000 cases will be shipped next month by using the results of a simple regression of operating costs on cases shipped. (Round variable costs per unit to 2 decimal places. Do not round "Multiple R","R Square", Standard Error" values and other intermediate calculations to nearest whole number.)

d-1. Enter the regression coefficients. (Round "Cases" and "Price Index" to 2 decimal places.)

d-2. Compute an estimate of operating costs assuming that 450,000 cases will be shipped next month by using the results of a multiple regression of operating costs on cases shipped and the price level. Assume a price level of 141 for next month. (Round variable costs per unit to 2 decimal places. Do not round "Multiple R","R Square", Standard Error" values and other intermediate calculations to nearest whole number.)