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Business Forecasting;Using the United Kingdom statistics locates Banks consumer credit: Gross lending figures from 1993-2003
Predictors: (Constant), LAGS(DATA,14), LAGS(DATA,4), LAGS(DATA,10), LAGS(DATA,12), LAGS(DATA,3), LAGS(DATA,1), LAGS(DATA,13)
This explains 95.7% of the variability and so will be reasonable fit to the data
Coefficients
Unstandardized Coefficients Standardized Coefficients t Sig.
Model B Std. Error Beta
1 (Constant) 391.580 210.597 1.859 .067
LAGS(DATA,1) 1.658E-02 .122 .017 .136 .892
LAGS(DATA,3) .310 .102 .301 3.042 .003
LAGS(DATA,4) 1.730E-03 .099 .002 .017 .986
LAGS(DATA,10) -.121 .103 -.112 -1.179 .242
LAGS(DATA,12) .593 .105 .547 5.663 .000
LAGS(DATA,13) 6.329E-02 .134 .059 .471 .639
LAGS(DATA,14) .196 .104 .181 1.883 .064
a Dependent Variable: DATA
From the coefficients table, the lag1, lag4, lag10, lag13, and lag14 data are not significant as well as the constant so the regression should be repeated only with lag3 and lag12 data because their significant is less than .05
Variables Entered/Removed
Model Variables Entered Variables Removed Method
1 LAGS(DATA,12), LAGS(DATA,3) . Enter
a All requested variables entered.
b Dependent Variable: DATA
c Linear Regression through the Origin
Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1