Using Multiple Regression Results to Construct and Apply a Cost Formula

The controller for Dohini Manufacturing Company felt that the number of purchase orders alone did not explain the monthly purchasing cost. He knew that nonstandard orders (for example, one requiring an overseas supplier) took more time and effort. He collected data on the number of nonstandard orders for the past 12 months and added that information to the data on purchasing cost and total number of purchase orders.

Month		Purchasing Cost		Number of Purchase Orders		Number of Nonstandard Orders
January		$18,860		370		53
February		18,065		330		35
March		19,250		370		61
April		18,050		410		14
May		19,345		400		73
June		19,500		450		55
July		19,670		460		30
August		20,940		560		80
September		19,430		440		51
October		20,020		500		50
November		18,800		470		12
December		19,340		480		27

Multiple regression was run on the above data; the coefficients shown by the regression program are:

Intercept	14,470 (rounded to the nearest dollar)
X variable 1	8.79 (rounded to the nearest cent)
X variable 2	20.35 (rounded to the nearest cent)

Required:

1. Construct the cost formula for the purchasing activity showing the fixed cost and the variable rate.

$

+

($ Purchase orders)

+

($ Nonstandard orders)

2. If Dohini Manufacturing Company estimates that next month will have 420 total purchase orders and 45 nonstandard orders, what is the total estimated purchasing cost for that month? (Round your answer to the nearest dollar.)

$

3. What if Dohini Manufacturing wants to estimate purchasing cost for the coming year and expects 5,350 purchase orders and 590 nonstandard orders?

What will estimated total purchasing cost be? (Round your answer to the nearest dollar.)

$

What is the total fixed purchasing cost?

$

Why doesn't it equal the fixed cost calculated in Requirement 2 above?