Module 11 Homework Use complete sentences. Show and label all work to receive an

Question

Module 11 Homework Use complete sentences. Show and label all work to receive any cr credit for the homework 4. High Low Cost Estimation: EastStar Energy has incurred the following maintenance oier to determine service vehicles for the first half of the year. cost behavior for the company. EastStar uses miles logged as their cost anve Month January February March April May June Total Miles Logged Maintenance Cost $24,300 14,200 13,240 16,800 8,600 10,100 12,240 23,460 18,600 17.640 22,100 Required a. Use the high-low cost estimation method to determine the expected cost if 11,000 miles are logged In one month Would it be okay to use the cost estimation equation you determined in a. above to predict costs at 18,000 miles? b. How about 9,000 miles? 5. The data from problem 4 above was entered into a regression program providing the following output Intercept 11,448.58 R Square X coefficient 0.7849 Standard error 0.2239 0.7545 A graph of the above data illustrates the regression line: Maintenance Cost $30,000 $25,000 $20,000 $15,000 $10,000 $5,000 $o 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 Required: a. Determine the cost estimation equation. b. How accurate is this cost estimation equation? c. Is miles logged an accurate predictor of maintenance costs? d. What would the estimated maintenance costs be at 11,000 miles? e. The result in d. above differs from the answer provided by the Hi-Lo estimation method. Module Homework 11-2

Explanation / Answer

Using the High- Low cost method:

Month         Miles          Cost ($)

Jan              14200          24300

May            10100         17640

Difference 4100           6660

Var. rate = 6660/4100 = $ 1.624

FC = TC – VC

FC = 24300 – 1.624*14200 = $1239.20

For 11000 miles TC = 1239.2 + 1.624*11000 = 1239.2+17864 = $19103.20

Though 18000 miles is outside the range for developing the High – Low equation, it (the High- Low eq) is used to predict future costs based on historical costs and thus it can provide an approximate figure of the cost of maintenance for 18000 miles and so can it for 9000 miles though these may differ from actual figures when some data points such as the 9000 mile actual cost figure does not fit the equation developed closely.

B. Regression Analysis:

Line of best fit is – Y = a+bX

Where a= 11448.58

Coefficient of X is 0.7849

Therefore, Y = 11448.58 +0.7849X

For 11000 miles the TC = 11448.58 + 0.7849*11000 = $ 20,082.48

The line of best fit through regression is more accurate as it has a mechanism to balance out data points that do not fall on the regression line. However, in this instance there are data points that do not conform to the maintenance cost – miles traveled relationship and are anomalies may be because of other intervening variables, unknown.

The graph and the calculation using the line of best fit for the maintenance cost of 11000 miles traveled are in agreement.   

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