Question

Problem 4

The following data exists for Lawrence Repair, a large equipment repair company. The behavior pattern of the maintenance overhead costs must be determined to prepare the annual profit plan for next year. The cost accountant has suggested using statistical analysis to derive an equation in the form of y=mx+b for maintenance overhead costs. Monthly data regarding past parts costs, repair hours and overhead costs are provided below.

Month	Overhead Costs	Parts Cost	Repair Hours
1	9896	1068	250
2	9249	1455	250
3	13205	3503	482
4	10560	1371	286
5	9059	1547	202
6	10667	1225	382
7	12888	2989	570
8	10350	1844	346
9	11222	1657	450
10	13274	2103	546
11	10835	1248	342
12	12612	2703	414
13	10876	2203	386
14	12821	3113	406
15	8469	755	214

Prepare a graphical representation of overhead cost estimation using Parts Cost as the independent variable. Using Repair Hours as the independent variable. For both scatterplots, use good formatting to include a Figure Title, Axis labels, trend line and remove blank area on the left half of the chart at a minimum.

Compute and report the simple regression results for each of the independent variables.

Report the following from your two outputs	Parts Cost	Repair Hours
Cost Equation using regression output
Predict overhead costs for $3500 parts cost & 480 repair hours
How much of the change in overhead can be explained?
Indicate the t-statistics, is is good?
Indicate the p-value, is is good?
Construct a 95% confidence interval for the estimated coefficient.
Which activity (parts cost or repair hours) do you believe best explains the variation in overhead costs? Provide your justification from the chart.

Compute and report a multiple regression analysis using both independent variables to explain the variation in costs. Provide a single cost equation using both independent variables.

Based on the single cost equation derived from the regression analysis, predict overhead costs for $3500 parts cost & 480 repair hours.

What is the percent of the total variance that can be explained by the regression equation?

Answer 1