Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow:

Month	Machine Hours	Electricity Costs
January	2,800	$	19,350
February	3,200	$	22,900
March	2,200	$	14,450
April	3,400	$	24,900
May	4,100	$	29,200
June	3,600	$	23,900
July	4,400	$	25,700
August	3,800	$	23,700
September	2,300	$	17,400
October	4,000	$	27,900
November	5,200	$	32,900
December	4,900	$	28,700

Summary Output
Regression Statistics
Multiple R	0.945
R Square	0.893
Adjusted R2	0.882
Standard Error	1,804.81
Observations	12.00

	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	4,979.52	2,173.65	2.29	0.04	136.32	9,822.72
Machine Hours	5.27	0.58	9.13	0.00	3.98	6.55

If the controller uses regression analysis to estimate costs, the cost equation for electricity costs is:

Multiple Choice

• Electricity Costs = $1,804.81 + ($12.00 Machine-hours).

• Electricity Costs = $2,173.65 + ($0.58 Machine-hours).

• Electricity Costs = $4,979.52 + ($2,173.65 Machine-hours).

• Electricity Costs = $4,979.52 + ($5.27 Machine-hours).

Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow:

Month	Machine Hours	Electricity Costs
January	3,400	$	18,850
February	3,800	$	21,900
March	2,800	$	13,950
April	4,000	$	23,900
May	4,700	$	28,700
June	4,200	$	22,900
July	5,300	$	25,200
August	4,400	$	23,200
September	2,900	$	16,400
October	4,600	$	26,900
November	6,500	$	31,900
December	5,800	$	28,200

Summary Output
Regression Statistics
Multiple R	0.928
R Square	0.862
Adjusted R2	0.848
Standard Error	2,039.35
Observations	12.00

	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	4,492.22	2,479.75	1.81	0.10	(1,033.00)	10,017.44
Machine Hours	4.35	0.55	7.89	0.00	3.12	5.58

The correlation coefficient for the regression equation for electricity costs is:

Multiple Choice

• 0.848.

• 0.912.

• 0.928.

• 0.862.

Brewsky's is a chain of micro-breweries. Managers are interested in the costs of the stores and believe that the costs can be explained in large part by the number of customers patronizing the stores. Monthly data regarding customer visits and costs for the preceding year for one of the stores have been entered into the regression analysis and the analysis is as follows:

Average monthly customer visits		1,702
Average monthly total costs	$	4,929
Regression Results
Intercept	$	1,736
b coefficient	$	2.40
R2		0.89234

What is the percent of the total variance that can be explained by the regression equation? (CMA adapted)

Multiple Choice

• 98.0%

• 29.0%

• 72.3%

• 89.2%