Multiple Linear Regression - Estimated Regression Equation
TIMEin[t] = + 1219.84629652389 -1.17141485359846DATE[t] + 1.94073888650875TEMP[t] -15.0904221241061RAIN[t] -0.00503232626156151BIRDS[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)1219.846296523894.931254247.370400
DATE-1.171414853598460.177255-6.60874e-062e-06
TEMP1.940738886508750.4899083.96140.0010080.000504
RAIN-15.09042212410614.385216-3.44120.0031170.001558
BIRDS-0.005032326261561510.004695-1.07180.2987950.149397


Multiple Linear Regression - Regression Statistics
Multiple R0.901396032504719
R-squared0.812514807415248
Adjusted R-squared0.76840064445413
F-TEST (value)18.41845686002
F-TEST (DF numerator)4
F-TEST (DF denominator)17
p-value5.22632880284313e-06
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation6.89881638867686
Sum Squared Residuals809.0923485995


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
111921203.67068591505-11.6706859150458
211961192.159065241733.84093475827361
311831194.01743557117-11.0174355711655
412101201.209641351648.79035864835658
512101209.070952451020.92904754897962
612181210.657140428687.34285957132274
712191218.260646604670.739353395325344
812021193.315287646188.68471235381585
911951192.767575215052.2324247849497
1012031202.464529115860.535470884142716
1111701178.08100995452-8.08100995451672
1211891184.759924803764.24007519624311
1311991197.189051119431.8109488805682
1411961201.06243455669-5.06243455668915
1511891184.373319351664.62668064833723
1611851196.90816011133-11.9081601113269
1711921189.301437945712.69856205429072
1811881184.469852813183.53014718682504
1911761179.88640244672-3.88640244671591
2011661163.01910246442.98089753560389
2111761175.373325052640.626674947362246
2211811182.98301983894-1.98301983893664