Multiple Linear Regression - Estimated Regression Equation
y[t] = + 269391918367.347 + 10333172541.7440x[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)269391918367.347540752911.851411498.179300
x10333172541.74401262926712.785788.181900


Multiple Linear Regression - Regression Statistics
Multiple R0.731977932899313
R-squared0.535791694251551
Adjusted R-squared0.52778810277313
F-TEST (value)66.9439083311658
F-TEST (DF numerator)1
F-TEST (DF denominator)58
p-value3.03712610616458e-11
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3785270382.95988
Sum Squared Residuals8.31039768582566e+20


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
12.63418e+11269391918367.347-5973918367.34745
22.62752e+11269391918367.347-6639918367.34693
32.66433e+11269391918367.347-2958918367.34693
42.67722e+11269391918367.347-1669918367.34693
52.66003e+11269391918367.347-3388918367.34693
62.62971e+11269391918367.347-6420918367.34693
72.65521e+11269391918367.347-3870918367.34693
82.64676e+11269391918367.347-4715918367.34693
92.70223e+11269391918367.347831081632.653072
102.69508e+11269391918367.347116081632.653072
112.68457e+11269391918367.347-934918367.346928
122.65814e+11269391918367.347-3577918367.34693
132.6668e+11269391918367.347-2711918367.34693
142.63018e+11269391918367.347-6373918367.34693
152.69285e+11269391918367.347-106918367.346928
162.69829e+11269391918367.347437081632.653072
172.70911e+11269391918367.3471519081632.65307
182.66844e+11269391918367.347-2547918367.34693
192.71244e+11269391918367.3471852081632.65307
202.69907e+11269391918367.347515081632.653072
212.71296e+11269391918367.3471904081632.65307
222.70157e+11269391918367.347765081632.653072
232.71322e+11269391918367.3471930081632.65307
242.67179e+11269391918367.347-2212918367.34693
252.64101e+11269391918367.347-5290918367.34693
262.65518e+11269391918367.347-3873918367.34693
272.69419e+11269391918367.34727081632.653072
282.68714e+11269391918367.347-677918367.346928
292.72482e+11269391918367.3473090081632.65307
302.68351e+11269391918367.347-1040918367.34693
312.68175e+11269391918367.347-1216918367.34693
322.70674e+11269391918367.3471282081632.65307
332.72764e+11269391918367.3473372081632.65307
342.72599e+11269391918367.3473207081632.65307
352.70333e+11269391918367.347941081632.653072
362.70846e+11269391918367.3471454081632.65307
372.70491e+11269391918367.3471099081632.65307
382.6916e+11269391918367.347-231918367.346928
392.74027e+11269391918367.3474635081632.65307
402.73784e+11269391918367.3474392081632.65307
412.76663e+11269391918367.3477271081632.65307
422.74525e+11269391918367.3475133081632.65307
432.71344e+11269391918367.3471952081632.65307
442.71115e+11269391918367.3471723081632.65307
452.70798e+11269391918367.3471406081632.65307
462.73911e+11269391918367.3474519081632.65307
472.73985e+11269391918367.3474593081632.65307
482.71917e+11269391918367.3472525081632.65307
492.73338e+11269391918367.3473946081632.65307
502.70601e+11279725090909.091-9124090909.09091
512.73547e+11279725090909.091-6178090909.09091
522.75363e+11279725090909.091-4362090909.09091
532.81229e+11279725090909.0911503909090.90909
542.77793e+11279725090909.091-1932090909.09091
552.79913e+11279725090909.091187909090.90909
562.825e+11279725090909.0912774909090.90909
572.80041e+11279725090909.091315909090.90909
582.82166e+11279725090909.0912440909090.90909
592.90304e+11279725090909.09110578909090.9091
602.83519e+11279725090909.0913793909090.90909