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MULTIPLE REGRESSION
The least square regression equation discussed above was based on the assumption that total cost was determined by only one activity based variable. However, other variables are likely to affect labour costs such as labour hours, material costs, machine hours, etc. These may have an effect on labour costs.
The equation for the simple regression can be expanded to include more than one independent variable as shown below:
Y = a + b1X1 + b2 X2 + b3 X3 +………+bn Xn
For two independent variables, the function will be of the form:
Y = a + b1X1 + b2 X2
The normal equations can be given by:∑y = na + b1 ∑X1 + b2∑x2∑X1Y = a∑x1 + b1∑X12 + b2 ∑X1 ∑X2∑X2 Y = a∑x2 + b1∑ X 1∑X2 +b2 ∑X2 Normally computers are used for the solution of multiple regression.
Computing equivalents units and assigning costs to completed units and ending work in process; no beginning inventory or cost transferred in (30 -45min) Sue Electronics makes CD p
Correlation coefficient (r) Correlation coefficient measures the degree of association between two variables such as the cost and the activity level. r = nΣxy - Σx Σy
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