Multiple Linear Regression - Estimated Regression Equation
y[t] = + 111.713076923077 + 7.47932692307695x[t] -10.3282692307694M1[t] -12.2482692307693M2[t] -0.524134615384614M3[t] -11.4641346153846M4[t] -11.9241346153846M5[t] -2.98000000000001M6[t] -15.8800000000000M7[t] -11.9M8[t] + 4.69999999999999M9[t] + 2.93999999999999M10[t] -1.98000000000001M11[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)111.7130769230773.02644336.912300
x7.479326923076950.9175258.151600
M1-10.32826923076943.760734-2.74630.0085140.004257
M2-12.24826923076933.760734-3.25690.0020940.001047
M3-0.5241346153846143.747279-0.13990.889360.44468
M4-11.46413461538463.747279-3.05930.0036580.001829
M5-11.92413461538463.747279-3.18210.0025920.001296
M6-2.980000000000013.742783-0.79620.429920.21496
M7-15.88000000000003.742783-4.24280.0001035.1e-05
M8-11.93.742783-3.17950.0026110.001306
M94.699999999999993.7427831.25570.2154140.107707
M102.939999999999993.7427830.78550.4360960.218048
M11-1.980000000000013.742783-0.5290.5992830.299641


Multiple Linear Regression - Regression Statistics
Multiple R0.877616207306407
R-squared0.770210207326883
Adjusted R-squared0.711540473027364
F-TEST (value)13.1278966322708
F-TEST (DF numerator)12
F-TEST (DF denominator)47
p-value3.05591107974124e-11
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation5.91786013143165
Sum Squared Residuals1645.99022115385


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
199.9101.384807692308-1.48480769230812
298.299.4648076923077-1.26480769230774
3104.5111.188942307692-6.68894230769227
4100.8100.2489423076920.55105769230774
5101.599.78894230769231.71105769230773
6103.9108.733076923077-4.83307692307689
799.695.8330769230773.76692307692307
898.499.8130769230769-1.41307692307689
9112.7116.413076923077-3.7130769230769
10118.4114.6530769230773.7469230769231
11108.1109.733076923077-1.63307692307690
12105.4111.713076923077-6.3130769230769
13114.6101.38480769230813.2151923076924
14106.999.46480769230777.43519230769235
15115.9118.668269230769-2.76826923076923
16109.8107.7282692307692.07173076923077
17101.8107.268269230769-5.46826923076923
18114.2123.691730769231-9.49173076923078
19110.8110.7917307692310.00826923076922678
20108.4114.771730769231-6.37173076923078
21127.5131.371730769231-3.87173076923078
22128.6129.611730769231-1.01173076923078
23116.6124.691730769231-8.09173076923078
24127.4126.6717307692310.728269230769223
25105116.343461538461-11.3434615384614
26108.3114.423461538462-6.12346153846154
27125126.147596153846-1.14759615384617
28111.6115.207596153846-3.60759615384617
29106.5114.747596153846-8.24759615384617
30130.3123.6917307692316.60826923076923
31115110.7917307692314.20826923076923
32116.1114.7717307692311.32826923076922
33134131.3717307692312.62826923076922
34126.5129.611730769231-3.11173076923077
35125.8124.6917307692311.10826923076923
36136.4126.6717307692319.72826923076922
37114.9116.343461538461-1.44346153846144
38110.9114.423461538462-3.52346153846153
39125.5126.147596153846-0.647596153846172
40116.8115.2075961538461.59240384615383
41116.8114.7475961538462.05240384615383
42125.5123.6917307692311.80826923076922
43104.2110.791730769231-6.59173076923076
44115.1114.7717307692310.328269230769217
45132.8131.3717307692311.42826923076923
46123.3129.611730769231-6.31173076923078
47124.8124.6917307692310.108269230769227
48122126.671730769231-4.67173076923079
49117.4116.3434615384611.05653846153857
50117.9114.4234615384623.47653846153847
51137.4126.14759615384611.2524038461538
52114.6115.207596153846-0.607596153846170
53124.7114.7475961538469.95240384615384
54129.6123.6917307692315.90826923076921
55109.4110.791730769231-1.39173076923076
56120.9114.7717307692316.12826923076923
57134.9131.3717307692313.52826923076923
58136.3129.6117307692316.68826923076923
59133.2124.6917307692318.50826923076922
60127.2126.6717307692310.52826923076922