Multiple Linear Regression - Estimated Regression Equation

2005[t] = -5.40392602506496 + 0.24512687720723`1992`[t] + 0.0127001368943751`2000`[t] + 0.676861788500026`2010`[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)	-5.40392602506496	1.380328	-3.915	0.00445	0.002225
`1992`	0.24512687720723	0.146299	1.6755	0.13236	0.06618
`2000`	0.0127001368943751	0.11335	0.112	0.913549	0.456775
`2010`	0.676861788500026	0.009684	69.8964	0	0

Multiple Linear Regression - Regression Statistics
Multiple R	0.99990745400614
R-squared	0.999814916577041
Adjusted R-squared	0.999745510293432
F-TEST (value)	14405.2507147781
F-TEST (DF numerator)	3
F-TEST (DF denominator)	8
p-value	2.88657986402541e-15
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.53954898240927
Sum Squared Residuals	51.5944722724476

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	139.633	139.528059747656	0.104940252343939
2	281.58	278.663907603732	2.91609239626772
3	144.053	144.233121391296	-0.180121391296209
4	246.16	244.670764847003	1.48923515299723
5	682.705	683.739353390303	-1.03435339030323
6	152.383	150.187603865742	2.19539613425786
7	100.903	100.661972041136	0.241027958863679
8	210.574	212.318428870095	-1.74442887009518
9	103.816	109.293881232607	-5.47788123260716
10	131.938	130.94129889989	0.99670110011001
11	262.611	262.962847518129	-0.351847518129338
12	141.263	140.417760592409	0.845239407590682