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# Cost Behavior

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### Cost Behavior

1. 1. Cost Behavior
2. 2. Cost Behavior • Variable • Fixed • Mixed
3. 3. Estimating Mixed Costs • Scattergraph method • Goal: Derive TC equation – Hi-Low analysis – Regression – Multiple Regression
4. 4. Interpreting Regression LO5 Interpret the results of regression output. F V Y = Intercept Y = Slope F + V X X
5. 5. Interpreting Regression, Continued. . . Correlation coefficient “R” measures the linear relationship between variables. The closer R is to 1.0 the closer the points are to the regression line. The closer R is to zero, the poorer the regression line. Coefficient of determination “R2” The square of the correlation coefficient. The proportion of the variation in the dependent variable (Y) explained by the independent variable(s)(X). T-Statistic The t-statistic is the value of the estimated coefficient, b, divided by its standard error. Generally, if it is over 2, then it is considered significant. If significant, the cost is NOT totally fixed.
6. 6. Interpreting Regression, Continued. . . Correlation Coefficient Coefficient of Determination T-Statistic .91 A linear relationship does exists between repair hours and overhead costs. .828 82.8% of the changes in overhead costs can be explained by changes in repair-hours. 10.7 & 7.9 Both have t-statistics that are greater than 2, so the cost is not totally fixed. Estimate 3C’s overhead with 520 repair hours.
7. 7. Multiple Regression Multiple Regression: When more than one predictor (x) is in the model. Is repair-hours the only activity that drives overhead costs at 3C? Predictors: X1: Repair-hours X2: Parts Cost Equation: TC = VC(X1) + VC(X2) + FC
8. 8. Multiple Regression, Continued. . . 3C Cost Information Month OH Costs Repair-Hours (X1) Parts (X2) 1 \$9,891 248 \$1,065 2 \$9,244 248 \$1,452 3 \$13,200 480 \$3,500 4 \$10,555 284 \$1,568 5 \$9,054 200 \$1,544 6 \$10,662 380 \$1,222 7 \$12,883 568 \$2,986 8 \$10,345 344 \$1,841 9 \$11,217 448 \$1,654 10 \$13,269 544 \$2,100 11 \$10,830 340 \$1,245 12 \$12,607 412 \$2,700 13 \$10,871 384 \$2,200 14 \$12,816 404 \$3,110 15 \$8,464 212 \$ 752
9. 9. Multiple Regression Output Interpret results and estimate total costs with 520 repair hours and \$3500 parts costs
10. 10. Statistical Cost Estimation Using Regression Analysis Statistical procedure to determine the relationship between variables. High-Low Method Regression Uses two data points. Uses all the data points. 3C Overhead
11. 11. Implementation Problems LO6 Identify potential problems with regression data. 1. Curvilinear costs 2. Outliers 3. Spurious relations Curvilinear costs 4. Assumptions Identify relevant range Analyze relevant range Relevant Range
12. 12. ICE Month Customer Accts Paychecks Proc Acct Svc Costs 1 325 1029 63800 2 310 993 68900 3 302 1268 64000 4 213 1028 61300 5 222 984 61600 6 214 712 50800 7 131 762 51020 8 123 739 54300 9 115 708 50500 10 296 1232 64800 11 213 978 58000 12 222 929 57500 13 217 1059 62200 14 132 942 54900 15 300 1299 71530 16 315 1283 64800 3650 15945 959950 Totals Required: Based on customer accounts, paychecks processed HiLo Analysis Regression Multiple Regression
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