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.

Month Purchasing Cost Number of Purchase Orders Number of Nonstandard Orders

January $$19,25037061$

February $18,05033040$

March $18,20032035$

April $18,05041014$

May $19,34540073$

June $19,50045055$

July $19,67046030$

August $20,94056080$

September $19,43044051$

October $20,02060075$

November $18,80047012$

December $19,34048027$

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

Intercept $14,490($rounded to the nearest dollar$)$

X variable $16\mathrm{.}30($rounded to the nearest cent$)$

X variable $216\mathrm{.}85($rounded to the nearest cent$)$

Required:

$2.$ If McGarvey Manufacturing Company estimates that next month will have $470$ total purchase orders and $42$ nonstandard orders, what is the total estimated purchasing cost for that month? $($Round your answer to the nearest dollar.$)$

$4$

$18,159$

$3.$ What if McGarvey Manufacturing wants to estimate purchasing cost for the coming year and expects $6,100$ purchase orders and $580$ nonstandard orders?

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

What is the total fixed purchasing cost?