Using Multiple Regression Results to Construct and Apply a Cost Formula The controller for McGarvey 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. Number of Number of Purchasing Purchase Nonstandard Month Cost Orders Orders January $19,250 370 61 February 18,050 330 40 March 18,200 320 35 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 20,020 600 75 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 14,610 (rounded to the nearest dollar) X variable 1 6.31 (rounded to the nearest cent) X variable 2 16.84 (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) + ($ x Nonstandard orders) 2. If McGarvey Manufacturing Company estimates that next month will have 480 total purchase orders and 42 nonstandard orders, what is the total estimated purchasing cost for that month? (Round your answer to the nearest dollar.) 3. What if McGarvey Manufacturing wants to estimate purchasing cost for the coming year and expects 6,020 purchase orders and 570 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