SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square 0.868519059 0.754325356 0.729757892 Standard Error 0.71684689 Observations 12 ANOVA Significance df MS F F Regression 1...

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

1. Is the model significant? What data demonstrates the significance of the model?


2. What does the R Square signify?


3. What is the forecast for period 13?

Extracted text: SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square 0.868519059 0.754325356 0.729757892 Standard Error 0.71684689 Observations 12 ANOVA Significance df MS F F Regression 1 15.77797 15.77797203 30.70424132 0.000247139 Residual 10 5.138695 0.513869464 Total 11 20.91667 Standard Error Coefficients 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 0.332167832 0.059946 5.541140796 0.000247139 0.198600381 0.465735283 0.198600381 0.465735283