Least squares Regression Analysis The managererit of Degerinc, is trying to develou a cost formula for its major manufacturing overtred activities. Disser's manufacturing process is highly automated and power cos.s are a significant manufacturing cost. Cost analysts have decided that power costs are mixed. The costs must be separated into their fixeu ant variable components so that the cost behavior of the power usage activity can be better understood. Analysts have determined that machine hours drive poner usage, thus machine tours are the cost driver for power custs. Nine months of data terve been collected and are presented in the chart beox Machine Period Hours Power Cost . 36.000 $45.000 FY $50320 540 $575.0 $50 3.21 $472511 $4141 Note: For the following recuirements, round the variable cos. 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 poner cast formula Power cost-$0 + $ x machine Hours! b. Use the mechas of least squares in Excel or a similar computer program to estimate a power cost formula Power cost $0 +O x Machine Hours c Pvaluate from requirements. Are machine hours a good predictor of praer costs? ONA, since 645 at variability in Prace costs is explained by machine hours, implics 365 of Paracer coats is driven by some other activity. A common rule of thumb is that a 'good' independent variable should explain aproximately 30% of the variability of a dependent variable. ONo, since 35% of variability in pone costs is explained by machine fouls, implies 54% of poner costs is driven by some olier activity. A common rule of hurbis Liat a good independent variable should explain approximately 30% of the variability of a dependent variable Ores, since 95 of variability in power costs is explained by machine hours, implies 54 of power costs is driven by some other activity. A common rule of thuma is that a "gaod" independent vanale should explain approximately 4109 of the variability of a nenendent variabe Cres 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 Bok of the variability of a dependent variabe d. Using the cost formula trom requirement b estimate power costs when 55,800 machine hour's are used INote: Round to the nearest callar, $0 Please answer all parts of the question Least squares Regression Analysis The managererit of Degerinc, is trying to develou a cost formula for its major manufacturing overtred activities. Disser's manufacturing process is highly automated and power cos.s are a significant manufacturing cost. Cost analysts have decided that power costs are mixed. The costs must be separated into their fixeu ant variable components so that the cost behavior of the power usage activity can be better understood. Analysts have determined that machine hours drive poner usage, thus machine tours are the cost driver for power custs. Nine months of data terve been collected and are presented in the chart beox Machine Period Hours Power Cost . 36.000 $45.000 FY $50320 540 $575.0 $50 3.21 $472511 $4141 Note: For the following recuirements, round the variable cos. 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 poner cast formula Power cost-$0 + $ x machine Hours! b. Use the mechas of least squares in Excel or a similar computer program to estimate a power cost formula Power cost $0 +O x Machine Hours c Pvaluate from requirements. Are machine hours a good predictor of praer costs? ONA, since 645 at variability in Prace costs is explained by machine hours, implics 365 of Paracer coats is driven by some other activity. A common rule of thumb is that a 'good' independent variable should explain aproximately 30% of the variability of a dependent variable. ONo, since 35% of variability in pone costs is explained by machine fouls, implies 54% of poner costs is driven by some olier activity. A common rule of hurbis Liat a good independent variable should explain approximately 30% of the variability of a dependent variable Ores, since 95 of variability in power costs is explained by machine hours, implies 54 of power costs is driven by some other activity. A common rule of thuma is that a "gaod" independent vanale should explain approximately 4109 of the variability of a nenendent variabe Cres 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 Bok of the variability of a dependent variabe d. Using the cost formula trom requirement b estimate power costs when 55,800 machine hour's are used INote: Round to the nearest callar, $0 Please answer all parts of the
