Regression Analysis: Cost Vs Output
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Describe each cost category as fixed or variable based upon the following simple regression results where cost is the dependent variable Y and output is the independent variable X.
**See attached spreadsheet for formulas and applicable data**
Output Cost1 ($) Cost2 ($) Cost3 ($)
0 17,000 11,000 0
100 10,000 7,000 1,000
200 8,000 13,000 2,000
500 20,000 10,000 6,000
900 14,000 12,000 10,000
1,000 8,000 19,000 11,000
1,200 15,000 16,000 13,000
1,300 14,000 15,000 15,000
1,400 6,000 16,000 18,000
1,500 18,000 23,000 19,000
1,700 8,000 21,000 22,000
1,900 16,000 25,000 24,000
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Solution Summary
The solution provides step by step method for the calculation of regression analysis. Formula for the calculation and Interpretations of the results are also included.
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Regression Analysis: Cost1 Vs Output
Output, X Cost1 ($), Y X^2 Y^2 XY
0 17,000 0 289000000 0
100 10,000 10000 100000000 1000000
200 8,000 40000 64000000 1600000
500 20,000 250000 400000000 10000000
900 14,000 810000 196000000 12600000
1,000 8,000 1000000 64000000 8000000
1,200 15,000 1440000 225000000 18000000
1,300 14,000 1690000 196000000 18200000
1,400 6,000 1960000 36000000 8400000
1,500 18,000 2250000 324000000 27000000
1,700 8,000 2890000 64000000 13600000
1,900 16,000 3610000 256000000 30400000
11700 1,54,000 15950000 2214000000 148800000
The general form of simple linear regression is Y= a + bX
Where Y is the dependent variable and X is the independent variable, a and be are known as the regression coefficients .They are estimated by the method of least squares. The estimates of a and b are given by
The parameter b measures the impact of unit change in X on the dependent variable Y. It is the slope of the regression line. The parameter a is the value of Y when X=0. It is known as the Intercept term.
The regression equation can be used to predict ...
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