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Method of Least Squares, Evaluation of Cost Equation Lassiter Company used the method of least squares to develop a cost equation to predict the cost of moving materials. There were 80 data points for the regression, and the following computer output was generated:
Intercept $17,350
Slope 12.00
Coefficient of correlation 0.92
Standard error $220
The activity driver used was the number of moves.
Required:
1. What is the cost formula?
2. Using the cost formula, predictthe costofmovingmaterialsif340movesaremade.Nowpreparea95 percent con?dence interval forth is prediction.(Round to the nearest dollar.)
3. What percentage of the variability in moving cost is explained by the number of moves? Do you think the equation will predict well? Why or why not?

Sagot :

Solution :

1). The cost of the formula is given as :

   $ 19,350 + $12 x

2). 95% [tex]\text{confidence interval}[/tex] for the prediction is :

    [tex]$21430 - 1.96 \times 220 < \text{Yf} < 21430+1.96 \times 220$[/tex]

     [tex]$20998.8 < \text{Yf} < 21861.2$[/tex]

     [tex]$20999 < \text{Yf} < 21861$[/tex]    (rounding off)

3). r = 0.92

Therefore, [tex]$r^2 = 0.8464$[/tex]

That is 84.64 % of the variability in the moving cost is best explained by the number of moves.

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