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.

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 $14,570($rounded to the nearest dollar$)$

X variable $16\mathrm{.}35($rounded to the nearest cent$)$

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

Required:

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

$fill in the blank $1$

$+($$fill in the blank $2$

$\backslash$times Purchase orders$)+($$fill in the blank $3$

$\backslash$times Nonstandard orders$)$

$2.$ If McGarvey Manufacturing Company estimates that next month will have $490$ total purchase orders and $42$ nonstandard orders, what is the total estimated purchasing cost for that month? $($Round your answer to the nearest dollar.$)$

$fill in the blank $4$

$3.$ What if McGarvey Manufacturing wants to estimate purchasing cost for the coming year and expects $6,100$ purchase orders and $600$ nonstandard orders?

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

$fill in the blank $5$

What is the total fixed purchasing cost?

$fill in the blank $6$

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

$\backslash$table$[[$Month$,\backslash$table$[[$Purchasing$],[$Cost$]],\backslash$table$[[$Number of$],[$Purchase$],[$Orders$]],\backslash$table$[[$Number of$],[$Nonstandard$],[$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 $14,570($rounded to the nearest dollar$)$

$x$ variable $1,6\mathrm{.}35($rounded to the nearest cent$)$

$x$ variable $2,16\mathrm{.}85($rounded to the nearest cent$)$