Multiple Linear Regression - Estimated Regression Equation
A[t] = + 8215.60010190161 -0.121914808989571B[t] + 0.2369237126587C[t] -101.189041547279t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)8215.600101901612058.6444483.99080.001340.00067
B-0.1219148089895710.149066-0.81790.427140.21357
C0.23692371265870.1417731.67110.1168860.058443
t-101.18904154727950.978457-1.98490.0671030.033552


Multiple Linear Regression - Regression Statistics
Multiple R0.520550812196351
R-squared0.270973148078281
Adjusted R-squared0.114753108380769
F-TEST (value)1.73456074267402
F-TEST (DF numerator)3
F-TEST (DF denominator)14
p-value0.205786884736227
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation962.190885202705
Sum Squared Residuals12961358.1939403


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
185008435.1968674334964.8031325665114
283508635.4121310066-285.412131006599
383008507.07776553323-207.077765533229
484008076.75885787931323.24114212069
590008528.05073313433471.949266865676
683008298.280125954871.71987404512914
770008126.01397060998-1126.01397060998
8103008386.062408882251913.93759111775
971507906.81430391666-756.814303916655
1081007862.5146025371237.4853974629
1172007472.1369712079-272.136971207898
1260007516.56230988475-1516.56230988475
1367507287.24158424612-537.241584246121
1492007417.690679779031782.30932022097
1576007384.65325719857215.346742801426
1670007373.11125783887-373.111257838867
1782887578.53871554869709.461284451305
1884009045.88345740826-645.883457408258