Multiple Linear Regression - Estimated Regression Equation
y [t] = + 2324.06337310277 -226.385033602657 x -451.374973256309 M1 -635.461053323771 M2 -583.133697991392 M3 -694.556342659014 M4 -555.478987326639 M5 -609.464131994259 M6 -532.074276661885 M7 -515.434421329508 M8 -460.85706599713 M9 -319.717210664754 M10 -118.389855332377 M11 -1.76485533237686 t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)2324.0633731027744.029939200158752.78370616270121.19694569468549e-1105.98472847342747e-111
x-226.38503360265741.0372264217049-5.516577345561551.20292777169205e-076.01463885846025e-08
M1-451.37497325630953.9429188998096-8.367640877844711.67221269262829e-148.36106346314144e-15
M2-635.46105332377153.9414791937995-11.78056410060074.69922120875431e-242.34961060437715e-24
M3-583.13369799139253.9312872347523-10.81253068285072.87306643189068e-211.43653321594534e-21
M4-694.55634265901453.9221664805898-12.88072026759222.98753690204156e-271.49376845102078e-27
M5-555.47898732663953.9141174749652-10.30303403527988.07738823933078e-204.03869411966539e-20
M6-609.46413199425953.9071406979543-11.30581448215061.10404950633647e-225.52024753168235e-23
M7-532.07427666188553.9012365659136-9.87128145031021.32473086791886e-186.6236543395943e-19
M8-515.43442132950853.8964054313543-9.563428529310669.54296124458896e-184.77148062229448e-18
M9-460.8570659971353.8926475828389-8.551390341117375.43649352166901e-152.71824676083450e-15
M10-319.71721066475453.8899632448941-5.932778413892241.51882754753869e-087.59413773769347e-09
M11-118.38985533237753.8883525779441-2.196947014870010.02931584965288860.0146579248264443
t-1.764855332376860.240551429858131-7.336706888076747.46953991690861e-123.73476995845430e-12


Multiple Linear Regression - Regression Statistics
Multiple R0.861322441473346
R-squared0.741876348185605
Adjusted R-squared0.723024620805902
F-TEST (value)39.3532291891914
F-TEST (DF numerator)13
F-TEST (DF denominator)178
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation152.417759557721
Sum Squared Residuals4135148.87028996