Least Squares Regression Analysis The management of Digger Inc., is trying to develop a cost formula for
Question:
Least Squares Regression Analysis
The management of Digger Inc., is trying to develop a cost formula for its major manufacturing overhead activities. Diggers manufacturing process is highly automated and power costs are a significant manufacturing cost. Cost analysts have decided that power costs are mixed. The costs must be separated into their fixed and variable components so that the cost behavior of the power usage activity can be better understood. Analysts have determined that machine hours drive power usage; thus machine hours are the cost driver for power costs. Nine months of data have been collected and are presented in the chart below:
Period | Machine Hours | Power Cost |
---|---|---|
January | 36,000 | $45,000 |
February | 45,000 | $60,300 |
March | 54,000 | $67,500 |
April | 39,600 | $53,064 |
May | 37,800 | $47,250 |
June | 32,400 | $43,416 |
July | 43,200 | $54,000 |
August | 50,400 | $67,536 |
September | 46,800 | $58,500 |
Note: For the following requirements, round the variable cost per unit to the nearest cent and the total fixed cost to the nearest dollar.
Required
a. Use the high and low points to estimate a power cost formula.
Power cost = $Answer
+ ($Answer
x machine hours)
b. Use the method of least squares in Excel or a similar computer program to estimate a power cost formula.
Power cost = $Answer
+ ($Answer
x machine hours)
c. Evaluate R2 from requirement b. Are machine hours a good predictor of power costs?
No, since 64% of variability in power costs is explained by machine hours, implies 36% of power costs is driven by some other activity. A common rule of thumb is that a "good" independent variable should explain approximately 80% of the variability of a dependent variable.
No, since 36% of variability in power costs is explained by machine hours, implies 64% of power costs is driven by some other activity. A common rule of thumb is that a "good" independent variable should explain approximately 80% of the variability of a dependent variable.
Yes, since 95% of variability in power costs is explained by machine hours, implies 5% of power costs is driven by some other activity. A common rule of thumb is that a "good" independent variable should explain approximately 80% of the variability of a dependent variable.
Yes, since 5% of variability in power costs is explained by machine hours, implies 95% of power costs is driven by some other activity. A common rule of thumb is that a "good" independent variable should explain approximately 80% of the variability of a dependent variable.
d. Using the cost formula from requirement b, estimate power costs when 55,800 machine hours are used.
(Note: Round to the nearest dollar.)
$Answer