Multiple Linear Regression - Estimated Regression Equation

Cons[t] = + 130.706587487140 + 1.06170962850255Inc[t] -1.38298545741215Price[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STAT H0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	130.706587487140	27.094293	4.8241	0.00027	0.000135
Inc	1.06170962850255	0.266674	3.9813	0.001365	0.000683
Price	-1.38298545741215	0.083814	-16.5006	0	0

Multiple Linear Regression - Regression Statistics
Multiple R	0.97533669567652
R-squared	0.951281669933193
Adjusted R-squared	0.944321908495077
F-TEST (value)	136.683085820079
F-TEST (DF numerator)	2
F-TEST (DF denominator)	14
p-value	6.51398490703059e-10
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	5.56335573538938
Sum Squared Residuals	433.312978538859

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	99.2	93.6923773647087	5.5076226352913
2	99	96.4234577562831	2.57654224371687
3	100	98.5790045961792	1.42099540382082
4	111.6	116.781445075516	-5.18144507551595
5	122.2	122.451685450906	-0.251685450905763
6	117.6	122.909996278299	-5.3099962782986
7	121.1	123.045531883681	-1.94553188368099
8	136	135.425382894250	0.574617105750393
9	154.2	149.804169317876	4.39583068212367
10	153.6	152.057362453703	1.54263754629677
11	158.5	153.905448166484	4.59455183351612
12	140.6	145.557094958023	-4.95709495802323
13	136.2	145.097520583372	-8.89752058337242
14	168	161.584412169109	6.41558783089085
15	154.3	156.861421638295	-2.56142163829510
16	149	156.288651026975	-7.2886510269755
17	165.5	156.135038386339	9.36496161366076