Multiple Linear Regression - Estimated Regression Equation
a[t] = + 130.707 + 1.06171b[t] -1.38299c[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)+130.7 27.09+4.8240e+00 0.00027 0.000135
b+1.062 0.2667+3.9810e+00 0.001365 0.0006826
c-1.383 0.08381-1.6500e+01 1.433e-10 7.163e-11


Multiple Linear Regression - Regression Statistics
Multiple R 0.9753
R-squared 0.9513
Adjusted R-squared 0.9443
F-TEST (value) 136.7
F-TEST (DF numerator)2
F-TEST (DF denominator)14
p-value 6.514e-10
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation 5.563
Sum Squared Residuals 433.3


Menu of Residual Diagnostics
DescriptionLink
HistogramCompute
Central TendencyCompute
QQ PlotCompute
Kernel Density PlotCompute
Skewness/Kurtosis TestCompute
Skewness-Kurtosis PlotCompute
Harrell-Davis PlotCompute
Bootstrap Plot -- Central TendencyCompute
Blocked Bootstrap Plot -- Central TendencyCompute
(Partial) Autocorrelation PlotCompute
Spectral AnalysisCompute
Tukey lambda PPCC PlotCompute
Box-Cox Normality PlotCompute
Summary StatisticsCompute


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
1 99.2 93.69 5.508
2 99 96.42 2.577
3 100 98.58 1.421
4 111.6 116.8-5.181
5 122.2 122.5-0.2517
6 117.6 122.9-5.31
7 121.1 123-1.946
8 136 135.4 0.5746
9 154.2 149.8 4.396
10 153.6 152.1 1.543
11 158.5 153.9 4.595
12 140.6 145.6-4.957
13 136.2 145.1-8.898
14 168 161.6 6.416
15 154.3 156.9-2.561
16 149 156.3-7.289
17 165.5 156.1 9.365


Ramsey RESET F-Test for powers (2 and 3) of fitted values
> reset_test_fitted
	RESET test
data:  mylm
RESET = 5.4877, df1 = 2, df2 = 12, p-value = 0.0203
Ramsey RESET F-Test for powers (2 and 3) of regressors
> reset_test_regressors
	RESET test
data:  mylm
RESET = 1.3404, df1 = 4, df2 = 10, p-value = 0.3209
Ramsey RESET F-Test for powers (2 and 3) of principal components
> reset_test_principal_components
	RESET test
data:  mylm
RESET = 2.7033, df1 = 2, df2 = 12, p-value = 0.1073


Variance Inflation Factors (Multicollinearity)
> vif
       b        c 
1.033043 1.033043