1. © 2014 by McGraw-Hill Education. This is proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part.

2. PowerPoint Authors: Susan Coomer Galbreath, Ph.D., CPA Charles W. Caldwell, D.B.A., CMA Jon A. Booker, Ph.D., CPA, CIA Cynthia J. Rooney, Ph.D., CPA Copyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Cost Estimation Chapter 5

3. 5-3 Basic Cost Behavior Patterns LO 5-1 Understand the reasons for estimating fixed and variable costs. Costs Fixed costsVariable costs Total fixed costs do not change proportionately as activity changes. Per unit fixed costs change inversely as activity changes. Total variable costs change proportionately as activity changes. Per unit variable cost remain constant as activity changes. LO 5-1

4. 5-4 Engineering Estimates LO 5-2 Estimate costs using engineering estimates. Cost estimates are based on measuring and then pricing the work involved in a task. Identify the activities involved: – Labor – Rent – Insurance Estimate the time and cost for each activity. LO 5-2

5. 5-5 Account Analysis LO 5-3 Estimate costs using account analysis. Review each account comprising the total cost being analyzed. Identify each cost as either fixed or variable. FixedVariable LO 5-3

6. 5-6 Statistical Cost Estimation LO 5-4 Estimate costs using statistical analysis. Analyze costs within a relevant range, which is the limits within which a cost estimate may be valid. Relevant range for a projection is usually between the upper and lower limits (bounds) of past activity levels for which data is available. LO 5-4

7. 5-7 Scattergraph We use “eyeball judgment” to determine the intercept and slope of the line. LO 5-4

8. 5-8 Hi-Low Cost Estimation Fixed cost (F) = Total cost at highest activity –(Variable cost × Highest activity level) Total cost at lowest activity –(Variable cost × Lowest activity level) Variable cost per unit (V) = (Cost at highest activity level – Cost at lowest activity level) (Highest activity level – Lowest activity level) LO 5-4

9. 5-9 Interpreting Regression LO 5-5 Interpret the results of regression output. Independent variable: –The X term, or predictor –The activity that predicts (causes) the change in costs Activities: –Repair-hours Dependent variable: –The Y term –The dependent variable –The cost to be estimated Costs: –Overhead costs LO 5-5

10. 5-10 Interpreting Regression Correlation coefficient (R): This 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 fit of the regression line. Coefficient of determination (R 2 ): This is the square of the correlation coefficient. It is the proportion of the variation in the dependent variable (Y) explained by the independent variable(s) (X). LO 5-5

11. 5-11 LO 5-6 Identify potential problems with regression data. Effect of: –Nonlinear relations –Outliers –Spurious relations –Using data that do not fit the assumptions of regression analysis LO 5-6 Practical Implementation Problems

12. 5-12 Volume Cost 0 5 10 15 20 25 30 35 40 $800 $700 $600 $500 $400 $300 $200 $100 $0 Assumed actual cost function Relevant range Regression estimate Capacity The Effect of Nonlinear Relations LO 5-6 Practical Implementation Problems

13. 5-13 Computed regression line True regression line “Outlier” The Effect of Outliers on the Computed Regression LO 5-6 Practical Implementation Problems

14. 5-14 The Effect of Spurious Relations Problem: Using too many variables in the regression (i.e., using direct labor to explain materials costs). Although the association is very high, actually both are driven by output. Solution: Carefully analyze each variable and determine the relationship among all elements before using in the regression. LO 5-6 Practical Implementation Problems

15. 5-15 The Effect of Using Data That Do Not Fit the Assumptions of Regression Problem: If the assumptions in the regression are not satisfied, then the regression is not reliable. Solution: There is no clear solution. Limit time to help assure costs behavior remains constant, yet this causes the model to be weaker due to less data. LO 5-6 Practical Implementation Problems

16. 5-16 How an Estimation Method is Chosen LO 5-7 Evaluate the advantages and disadvantages of alternative cost estimation methods. Reliance on historical data is relatively inexpensive. Computational tools allow for more data to be used than for non-statistical methods. Reliance on historical data may be the only readily available, cost-effective basis for estimating costs. Analysts must be alert to cost-activity changes. LO 5-7

17. 5-17 Appendix A: Regression Analysis Using Microsoft Excel LO 5-8 (Appendix A) Use Microsoft Excel to perform a regression analysis. Many software programs exist to aid in performing regression analysis. Data is entered and the user then selects the data and type of regression analysis to be generated. The analyst must be well schooled in regression in order to determine the meaning of the output. In order to use Microsoft Excel, the Analysis Tool Pak must be installed. LO 5-8

18. 5-18 Appendix B: Learning Curves This is the systematic relationship between the amount of experience in performing a task and the time required to perform it. First unit Second unit Fourth unit Eighth unit 100.0 hours 80.0 hours 64.0 hours 51.2 hours (assumed) 80% × 100 hours 80% × 80 hours 80% × 64 hours Unit Time to produce Calculation of time Impact: It causes the unit price to decrease as production increases. This implies a nonlinear model. LO 5-9 (Appendix B) Understand the mathematical relationship describing the learning phenomenon. LO 5-9

19. 5-19 End of Chapter 5