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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.
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The F–test The significance of the regression results can be tested by using the F- statistics. The F-statistics is a ratio which compares the explained sum of squares and t
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THE BASIC EOQ MODEL This is the most simple of all the models discussed. In addition to the general assumptions which relate to all deterministic models (i.e. certainty of all
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