Multiple Linear Regression - Estimated Regression Equation
BBP[t] = + 208989.045454546 + 87691.3545454545`Ja/nee`[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)208989.0454545468049.75053825.962200
`Ja/nee`87691.354545454518705.9298644.68798.4e-054.2e-05


Multiple Linear Regression - Regression Statistics
Multiple R0.683971466701604
R-squared0.467816967261944
Adjusted R-squared0.446529645952422
F-TEST (value)21.9763191648110
F-TEST (DF numerator)1
F-TEST (DF denominator)25
p-value8.36695315282743e-05
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation37756.6767849897
Sum Squared Residuals35639166046.1545


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
1163414208989.045454545-45575.0454545452
2163652208989.045454545-45337.0454545454
3164603208989.045454545-44386.0454545455
4165257208989.045454545-43732.0454545455
5168731208989.045454545-40258.0454545455
6171848208989.045454545-37141.0454545455
7175032208989.045454545-33957.0454545455
8179187208989.045454545-29802.0454545455
9187369208989.045454545-21620.0454545455
10194147208989.045454545-14842.0454545455
11200145208989.045454545-8844.04545454547
12203750208989.045454545-5239.04545454547
13206464208989.045454545-2525.04545454547
14205034208989.045454545-3955.04545454547
15211782208989.0454545452792.95454545453
16244562208989.04545454535572.9545454545
17247059208989.04545454538069.9545454545
18255703208989.04545454546713.9545454545
19260218208989.04545454551228.9545454545
20268852208989.04545454559862.9545454545
21279436208989.04545454570446.9545454545
22281514208989.04545454572524.9545454545
23285458296680.4-11222.4
24288338296680.4-8342.40000000001
25296369296680.4-311.400000000009
26302221296680.45540.59999999999
27311016296680.414335.6