horngren_ima15_im 03.doc

B account analysis selects a volume related cost

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B. Account Analysis - selects a volume-related cost driver and classifies each account from the accounting records as a variable or fixed cost. The cost analyst then looks at each cost account balance and estimates either the variable cost per unit of cost driver activity or the periodic fixed cost. C. High-Low, Visual Fit, and Least-Squares Methods These methods rely on the use of past cost data to predict costs. These methods may not be particularly useful in predicting costs for changing organizations. If these methods are used, the cost analyst must be careful that the historical data that is from a past environment is not obsolete. Historical data may hide past inefficiencies that could be reduced if they are identified. 1. High-Low Method - makes use of the costs and activity levels for the high and low activity levels in a set of data (unless one of these levels is viewed as an outlier). The difference in costs for the two activity levels is divided by the difference in activity levels to determine the variable cost per unit of activity. Then, either the high activity level and the cost at that activity level or the low activity level and the cost at that activity are used to solve for the fixed cost. Due to its reliance on just two data points, this method is rarely used in practice (see EXHIBIT 3-4 ). 2. Visual-Fit Method - more reliable than the high-low method because all the available data are used. In the visual fit method, the cost analyst visually fits a straight line through a plot of all of the available data. The line is extended back until it intersects the vertical axis of the graph. The analyst measures where the line intersects the cost axis to estimate the fixed cost. An activity level is selected and the mixed cost at that activity level is used to determine the variable cost per unit of activity by subtracting fixed cost from mixed cost and dividing by the activity level. The subjectivity in placing the line and in estimating the fixed and variable costs are disadvantages of this method and is rarely used in practice (see EXHIBIT 3-5 ). 36
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3. Least-Squares Regression Method – (or simply regression analysis) uses statistics to fit a cost function to all the data. Using one cost driver requires simple regression, while using more than one cost driver requires the use of multiple regression . Regression analysis usually measures cost behavior more reliably than other cost measurement methods. In addition, regression analysis yields important statistical information about the reliability of cost estimates so analysts can assess confidence in the cost measures and select the best cost driver. Coefficient of Determination (R 2 ) - measures how much of the fluctuation of a cost is explained by changes in the cost driver (see EXHIBIT 3-6 ).
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