Question

The following information on maintenance and repair costs and revenues for the last two years is available from the accounting records at Arnie’s Arcade & Video Palace. Arnie has asked you to help him understand the relation between business volume and maintenance and repair cost.

Month	Maintenance and Repair Cost ($000)	Revenues ($000)
July	$1.86	$50.00
August	2.83	44.00
September	2.35	40.00
October	1.76	56.00
November	1.85	68.00
December	0.69	96.00
January	2.67	36.00
February	2.71	42.00
March	2.57	52.00
April	2.53	54.00
May	1.59	58.00
June	1.33	70.00
July	2.15	64.00
August	1.57	58.00
September	2.12	66.00
October	1.93	68.00
November	0.98	78.00
December	0.31	108.00
January	2.13	52.00
February	1.83	54.00
March	1.24	74.00
April	1.50	78.00
May	1.50	64.00
June	1.60	60.00

Required:

Using Excel, estimate a linear regression with maintenance and repair cost as the dependent variable and revenue as the independent variable. (Negative amounts should be indicated by a minus sign. Round "Multiple R, R Square and Standard Error" to 7 decimal places, "Intercept and Revenues" to 4 decimal places.)

	Regression Statistics Multiple R R Square Standard Error Observations Coefficients Intercept Revenues

Answer 1

Answer:

.

Regression statistics

Multiple R	0.8852219
R square	0.7836178
Standard error	0.3041103
Observations	24

.

Coefficients

Intercept	3.9044
Revenues	-0.0336

.

The general form of linear regression equation is defined as

Y = b₀ + b₁ X

where Y = dependent variable = Maintenance and repair cost

X = independent variable = Revenues

b₀= intercept

b₁= slope

.

To obtain the values of intercept and slope, we have to perform regression analysis in excel.

In excel, go to Data tab and choose Data analysis and select Regression.

.

.

SUMMARY OUTPUT

.

Regression statistics

Multiple R	0.8852219
R square	0.7836178
Standard error	0.3041103
Observations	24

.
ANOVA.

	df	SS	MS	F	Significance F
Regression	1	7.368305846	7.368306	79.67194	0.000000009148
Residual	22	2.034627487	0.092483
Total	23	9.402933333

.

	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	3.904394	0.241993	16.13436	0.000000000000112	3.4025326	4.406256	3.402533	4.406256
X Variable 1	-0.03363	0.003767	-8.92591	0.00000000915	-0.041441	-0.02581	-0.04144	-0.02581