Answer:
(1) The cost formula is: <em>y</em> = $19,050 + $12·<em>x</em><em>.</em>
(2) The cost of moving materials if 340 moves are made is $23,130.
(3) 82.81% of the variability in moving cost is explained by the number of moves.
Step-by-step explanation:
The computer output for the regression analysis of 80 data points is as follows:
Intercept: $19,050
Slope: 12
Coefficient of correlation: 0.91
Standard error: $220
(1)
The general formula of regression equation is:
<em>y</em> = <em>a</em> + <em>b</em>·<em>x</em>
Here,
<em>a</em> = intercept
<em>b</em> = slope
The cost formula is:
<em>y</em> = $19,050 + $12·<em>x</em>
(2)
Predict the cost of moving materials if 340 moves are made as follows:
![y = 19050 + 12\cdot x\\=19050+12\times 340\\=19050+4080\\=23130](https://tex.z-dn.net/?f=y%20%3D%2019050%20%2B%2012%5Ccdot%20x%5C%5C%3D19050%2B12%5Ctimes%20340%5C%5C%3D19050%2B4080%5C%5C%3D23130)
Thus, the cost of moving materials if 340 moves are made is $23,130.
(3)
The coefficient of determination R² specifies the percentage of the variance in the dependent variable (Y) that is forecasted or explained by linear regression and the forecaster variable (X, also recognized as the independent-variable).
The coefficient of determination R² can be computed by squaring the correlation coefficient value.
![R^{2}=(r)^{2}=(0.91)^{2}=0.8281](https://tex.z-dn.net/?f=R%5E%7B2%7D%3D%28r%29%5E%7B2%7D%3D%280.91%29%5E%7B2%7D%3D0.8281)
Thus, 82.81% of the variability in moving cost is explained by the number of moves.