An organization develops a linear regression model to forecast sales.Below are the results of the regression analysis using 12 periods in the model.

The regression equation is Y = .332167832(X) + 12.42424242

SUMMARY OUTPUT Regression Statistics Multiple R 0.868519059 R Square 0.754325356 Adjusted R Square 0.729757892 Standard Error 0.71684689 Observations 12 ANOVA Significance 55 MS F F Regression 1 15.77797 15.77797203 30.70424132 0.000247139 Residual 10 5.138695 0.513869464 Total 11 20.91667 Standard Coefficients Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%% Intercept 12.42424242 0.441189 28.16083155 7.408E-11 11 4412126 13,40727225 11 4412126 13,40727225 X Variable 1 0.352167832 0.059946 5.541140796 0.000247139 0.198600381 0.465735283 0.198600381 0.465735283