Consider the following multiple regression model of domestic car sales (DCS) where:

 

DCS = domestic car sales

DCSP = domestic car sales price (in dollars)

PR = prime rate as a percent (i.e., 10% would be entered as 10)

Q2 = quarter 2 dummy variable

Q3 = quarter 3 dummy variable

Q4 = quarter 4 dummy variable

 

 

 

Multiple Regression — Result Formula

DCS = 3,266.66 + ((DCSP) × −0.098297) + ((PR) × −21.17) + ((Q2) × 292.88) + ((Q3) × 149.07) + ((Q4) × −60.25)

 

Audit Trail — ANOVA Table (Multiple Regression Selected)
Source of variation	SS			df			MS			SEE
Regression		1,834,180.23			5			366,836.05
Error		494,506.47			34			14,544.31			120.60
Total		2,328,686.70			39

 

Audit Trail — Coefficient Table (Multiple Regression Selected)
Series Description	Included in Model			Coefficient			Standard Error			T-test			P-value			F-test			Elasticity			Overall F-test
DCS		Dependent			3,266.66			288.10			11.34			0.00			128.56						25.22
DCSP		Yes			−0.10			0.01			−7.18			0.00			51.50			−0.76
PR		Yes			−21.17			13.77			−1.54			0.13			2.36			−0.11
Q2		Yes			292.88			54.02			5.42			0.00			29.39			0.04
Q3		Yes			149.07			54.11			2.76			0.01			7.59			0.02
Q4		Yes			−60.25			54.22			−1.11			0.27			1.23			−0.01

 

Audit Trail - Statistics
Accuracy Measures	Value		Forecast Statistics	Value
AIC	492.41		Durbin Watson	1.62
BIC	494.10		Mean	1,802.86
Mean Absolute Percentage Error (MAPE)	5.30	%	Standard Deviation	244.36
R-Square	78.76	%	Max	2,272.60
Adjusted R-Square	75.64	%	Min	1,421.30
Root Mean Square Error	111.19		Range	851.30

 

For the domestic car sales regression above, the "third quick check" shows what (i.e., accuracy)?

DCS 2500 2000 1500 1000 500 DCS Forecast of DCS Fitted Values an-84 an-85 Jan-86 an-87 Jan-88 Jan-89 Jan-90 an-91 Jan-92 Jan-93 Jan-94