in Table 7.1), create the apply and use it to estimate the value of a home having 3 full bathrooms, 2 half bathrooms, and 3,200 square feet overall. 5. The Multiple Correlation Coefficient The standard error is one way to summarize how good forecasts are from a multiple regression equation. Here we describe another very commonly used method. If you have a Y variable and a single X variable, the correlation coefficient is a good way to summarize how well the data fit a line on a scale from -1 to +1. When you have multiple X variables there are many different correlation coefficients you might look at: one for each pair of variables. The common practice for summarizing how well data fit a multiple regression equation is to compute the correlation between the forecasted Y values from the regression equation and the actual Y values. This is called the multipleSECTION 5. THE MULTIPLE CORRELATION COEFFICIENT 247 $5,000,000 R2 = 0.65 $4,000,000 $3,000,000 Actual Value $2,000,000 $1,000,000 $1,000,000 $2,000,000 $3,000,000 $4,000,000 $5,000,000 Forecasted Value Figure 7.2. The correlation between actual and forecasted values is the multiple correlation coefficient. otter R. Usually