Multiple Linear Regression - Estimated Regression Equation
x[t] = + 90.5447115384615 -25.7745192307692y[t] -4.96431490384618M1[t] -7.6396875M2[t] -6.47527644230769M3[t] -1.73564903846153M4[t] -2.79602163461538M5[t] -8.95639423076922M6[t] -4.54176682692307M7[t] -3.57713942307692M8[t] -5.38751201923077M9[t] -2.67288461538462M10[t] + 4.16037259615385M11[t] + 0.835372596153847t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)90.54471153846155.94383715.233400
y-25.77451923076925.860702-4.39799.3e-054.6e-05
M1-4.964314903846186.79567-0.73050.4698050.234903
M2-7.63968756.791382-1.12490.2680720.134036
M3-6.475276442307697.201539-0.89920.3745470.187273
M4-1.735649038461537.189155-0.24140.8105950.405297
M5-2.796021634615387.182397-0.38930.6993560.349678
M6-8.956394230769227.181282-1.24720.2203820.110191
M7-4.541766826923077.185812-0.6320.531350.265675
M8-3.577139423076927.195977-0.49710.6221390.31107
M9-5.387512019230777.211752-0.7470.4598870.229944
M10-2.672884615384627.233101-0.36950.7138940.356947
M114.160372596153857.1464410.58220.5640870.282044
t0.8353725961538470.2013694.14850.0001959.8e-05


Multiple Linear Regression - Regression Statistics
Multiple R0.64626567666583
R-squared0.417659324836343
Adjusted R-squared0.207369636582801
F-TEST (value)1.98611414713202
F-TEST (DF numerator)13
F-TEST (DF denominator)36
p-value0.0521115636155549
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation10.1025803605435
Sum Squared Residuals3674.23667788462


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
18586.4157692307693-1.41576923076932
287.684.57576923076923.02423076923075
388.686.57555288461542.02444711538463
49592.15055288461542.84944711538461
596.391.92555288461544.37444711538463
683.386.6005528846154-3.30055288461539
796.991.85055288461545.04944711538463
8103.493.65055288461549.74944711538462
999.392.67555288461546.62444711538462
10103.896.22555288461547.57444711538462
11113.4103.8941826923089.50581730769231
12111.5100.56918269230810.9308173076923
13114.296.440240384615417.7597596153847
1490.694.6002403846154-4.00024038461537
1590.896.6000240384615-5.80002403846155
1696.4102.175024038462-5.77502403846153
1790101.950024038462-11.9500240384615
1892.196.6250240384615-4.52502403846154
1997.2101.875024038462-4.67502403846154
2095.1103.675024038462-8.57502403846154
2188.5102.700024038462-14.2000240384615
2291106.250024038462-15.2500240384615
2390.588.14413461538462.35586538461539
247584.8191346153846-9.81913461538461
2566.380.6901923076923-14.3901923076923
266678.8501923076923-12.8501923076923
2768.480.8499759615385-12.4499759615385
2870.686.4249759615385-15.8249759615385
2983.986.1999759615385-2.29997596153846
3090.180.87497596153859.22502403846154
3190.686.12497596153854.47502403846153
3287.187.9249759615385-0.824975961538458
3390.886.94997596153853.85002403846154
3494.190.49997596153853.60002403846154
3599.898.16860576923081.63139423076923
3696.894.84360576923081.95639423076923
378790.7146634615384-3.71466346153844
3896.388.87466346153857.42533653846154
39107.190.874447115384616.2255528846154
40115.296.449447115384618.7505528846154
41106.196.22444711538469.87555288461537
4289.590.8994471153846-1.39944711538461
4391.396.1494471153846-4.84944711538463
4497.697.9494471153846-0.349447115384619
45100.796.97444711538463.72555288461538
46104.6100.5244471153854.07555288461538
4794.7108.193076923077-13.4930769230769
48101.8104.868076923077-3.06807692307693
49102.5100.7391346153851.76086538461539
50105.398.89913461538466.40086538461538