Question

Question 6. In your spreadsheet, calculate the estimated line maintenance expense that would be predicted by the regression function for each company in the sample. Plot the predicted values you calculate on your graph. Does is appear linear regression model is appropriate.

The Following table shows the calculations for regression line:

	Customers (in 1000s), X	Line Maintenance Expense (in $1000s), Y	X^2	Y^2	XY
	25.3	484.6	640.09	234837.16	12260.38
	36.4	672.3	1324.96	451987.29	24471.72
	37.9	839.4	1436.41	704592.36	31813.26
	45.9	694.9	2106.81	482886.01	31895.91
	53.4	836.4	2851.56	699564.96	44663.76
	66.8	681.9	4462.24	464987.61	45550.92
	78.4	1037	6146.56	1075369	81300.8
	82.6	1095.6	6822.76	1200339.36	90496.56
	93.8	1563.1	8798.44	2443281.61	146618.78
	97.5	1377.9	9506.25	1898608.41	134345.25
	105.7	1711.7	11172.49	2929916.89	180926.69
	124.3	2138.6	15450.49	4573609.96	265827.98
Total	848	13133.4	70719.06	17159980.62	1090172.01

Answer 1

Solution-

Let us plot the graphs by calculating the equation using a chart in the spreadsheet-

As we can see that the difference in predicted value and actual value is not much, we can say that the model is approapiate.