1	SUMMARY OUTPUT
2	Regression Statistics
3	Multiple R		0.92
4	R Square		0.84
5	Adjusted R Square	0.81
6	Standard Error	148.38
7	Observations	12
8	ANOVA
9		df	SS	MS	F	Significance F
10	Regression	1	573,116.90	573,116.90	26.03	0
11	Residual	10	110,083.10	22,016.62
12	Total	11	683,200.00
14		Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
15	Intercept	1,263.34	806.85	1.57	0.18	-810.75	3,337.42
16	X Variable 1	0.26	0.05	5.1	0	0.13	0.39

A legal firm wanted to determine the relationship between its monthly operating costs and a potential cost driver, professional hours. An excerpt from the output of a regression analysis performed using Excel showed the above information.

a. Given this output, write the legal firm's monthly cost equation. (Enter all amounts to the nearest cent, X.XX.)

The legal firm's monthly cost equation is: y =

x +

.

b.	Should management use this equation to predict monthly operating costs? Explain your answer