# 25_OverheadsForChen1 - Objectivesfortoday What are some...

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ACCY 302 (Chen) Fall 2009, Class 25 1 Objectives for today What are some questions regression can help us with? Cost estimation using regression analysis simple and multiple regression identify the form of regression equations identify estimated equations assess the goodness of fit test hypotheses assess the range of coefficients

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ACCY 302 (Chen) Fall 2009, Class 25 2 What are some questions  regression can help us with? If we're analyzing operations: Can we explain current levels of and/or changes in: sales input costs overhead costs nonfinancial measures of performance
ACCY 302 (Chen) Fall 2009, Class 25 3 What are some questions regression  can help us with?  (continued) If we're forecasting (e.g., for budgets) : Can we predict future levels of and/or changes in: sales input costs overhead costs nonfinancial measures of performance

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ACCY 302 (Chen) Fall 2009, Class 25 4 What are some questions regression  can help us with?  (continued) If we're focusing on costs : How will spending vary across different alternatives? What are the drivers of particular costs? Can we identify the variable and fixed components of costs?
ACCY 302 (Chen) Fall 2009, Class 25 5 Example: 0 500 1000 1500 2000 2500 0 50 100 150 200 250 Number of Suppliers Costs (in thousands) To solve, we can use: •  High-Low Method  (circled points) •  Regression Analysis  (all or some points) TC = FC + ( VC x units of cost driver )

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ACCY 302 (Chen) Fall 2009, Class 25 6 Cost estimation using regression  analysis Continuing our focus on costs: TC = FC + VC (X) where: TC = total cost FC = fixed cost (more precisely, costs that don't vary with changes in the cost driver) VC = variable cost per unit of cost driver X = units of cost driver (e.g., number of suppliers) slope intercept This is the equation  for a line!
ACCY 302 (Chen) Fall 2009, Class 25 7 Cost estimation using regression analysis   (continued) Repeating our formula: TC = FC + VC (X) TC represents expected (or estimated) total cost, which we can derive from regression For any actual observation of costs, the formula is: TC = FC + VC (X) + random variation

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ACCY 302 (Chen) Fall 2009, Class 25 8 Cost estimation using regression analysis   (continued) And formally, regression equations are of the form: Y = α + ( ß * X ) + ε where: Y = dependent variable (DV) (e.g., total costs) α = intercept (e.g., total fixed costs) ß = coefficient (e.g., variable cost per unit of cost driver) X = independent/predictor variable (IV) (e.g., units of cost driver) ε = random error
ACCY 302 (Chen) Fall 2009, Class 25 9 Simple linear regression

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## This note was uploaded on 11/08/2011 for the course ACCY 302 taught by Professor Staff during the Spring '08 term at University of Illinois, Urbana Champaign.

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25_OverheadsForChen1 - Objectivesfortoday What are some...

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