Multiple Linear Regression - Estimated Regression Equation
y[t] = + 1.48357142857143 -0.0407472111651671dummy[t] + 0.00359133126934983trend[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)1.483571428571430.005196285.538900
dummy-0.04074721116516710.079351-0.51350.6095830.304792
trend0.003591331269349830.001532.34770.0223870.011193


Multiple Linear Regression - Regression Statistics
Multiple R0.897701072443381
R-squared0.805867215465997
Adjusted R-squared0.79905553881568
F-TEST (value)118.306733692155
F-TEST (DF numerator)2
F-TEST (DF denominator)57
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.0336719156278326
Sum Squared Residuals0.064626480416729


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
11.431.48357142857144-0.053571428571436
21.431.48357142857143-0.0535714285714282
31.431.48357142857143-0.0535714285714285
41.431.48357142857143-0.0535714285714285
51.431.48357142857143-0.0535714285714285
61.431.48357142857143-0.0535714285714285
71.441.48357142857143-0.0435714285714284
81.481.48357142857143-0.00357142857142840
91.481.48357142857143-0.00357142857142840
101.481.48357142857143-0.00357142857142840
111.481.48357142857143-0.00357142857142840
121.481.48357142857143-0.00357142857142840
131.481.48357142857143-0.00357142857142840
141.481.48357142857143-0.00357142857142840
151.481.48357142857143-0.00357142857142840
161.481.48357142857143-0.00357142857142840
171.481.48357142857143-0.00357142857142840
181.481.48357142857143-0.00357142857142840
191.481.48357142857143-0.00357142857142840
201.481.48357142857143-0.00357142857142840
211.481.48357142857143-0.00357142857142840
221.481.48357142857143-0.00357142857142840
231.481.48357142857143-0.00357142857142840
241.481.48357142857143-0.00357142857142840
251.481.48357142857143-0.00357142857142840
261.481.48357142857143-0.00357142857142840
271.481.48357142857143-0.00357142857142840
281.481.48357142857143-0.00357142857142840
291.481.48357142857143-0.00357142857142840
301.481.48357142857143-0.00357142857142840
311.481.48357142857143-0.00357142857142840
321.481.48357142857143-0.00357142857142840
331.481.48357142857143-0.00357142857142840
341.481.48357142857143-0.00357142857142840
351.481.48357142857143-0.00357142857142840
361.481.48357142857143-0.00357142857142840
371.481.48357142857143-0.00357142857142840
381.571.483571428571430.0864285714285717
391.581.483571428571430.0964285714285717
401.581.483571428571430.0964285714285717
411.581.483571428571430.0964285714285717
421.581.483571428571430.0964285714285717
431.591.59725146198830-0.00725146198830409
441.61.60084279325765-0.000842793257653915
451.61.60443412452700-0.00443412452700375
461.611.608025455796350.00197454420364643
471.611.61161678706570-0.00161678706570341
481.611.61520811833505-0.00520811833505324
491.621.618799449604400.00120055039559693
501.631.622390780873750.00760921912624688
511.631.625982112143100.00401788785689705
521.641.629573443412450.0104265565875472
531.641.633164774681800.0068352253181974
541.641.636756105951150.00324389404884756
551.641.64034743722050-0.000347437220502276
561.641.64393876848985-0.00393876848985211
571.651.64753009975920.00246990024079807
581.651.65112143102855-0.00112143102855177
591.651.65471276229790-0.0047127622979016
601.651.65830409356725-0.00830409356725144