Regression Statistics Multiple R 0.894370114 R Square 0.799897902 Adjusted R Square 0.795244364 Standard Error 0.838089828 Observations 45 What does the R Square value indicate regarding the data?

The R Square value, also known as the coefficient of determination, indicates the proportion of the variance in the dependent variable that can be explained by the independent variables in the regression model. In your case, the R Square value is approximately 0.7999, or 79.99%. This means that about 80% of the variance in the dependent variable can be explained by the independent variables included in the model. This is generally considered a good fit, suggesting that the model explains a significant amount of the variance in the data. However, it's important to also consider the context of the data and the domain you are working in. An R Square value close to 1 indicates a very good fit, while a value closer to 0 suggests that the model does not explain much of the variance. Additionally, it is important to look at other metrics (like the Adjusted R Square, which accounts for the number of predictors in the model) and residual analysis to assess the model's performance comprehensively.