The given information does not provide the correlation coefficient value. However, in general, the closer the correlation coefficient is to 1 or -1, the more confident we can be in the accuracy of the predicted value using the line of best fit.
If the correlation coefficient is close to 1, then the relationship between the two variables is strong and positive. This means that as one variable increases, the other variable also tends to increase. On the other hand, if the correlation coefficient is close to -1, then the relationship between the two variables is strong and negative. This means that as one variable increases, the other variable tends to decrease.
If the correlation coefficient is close to 0, then there is no linear relationship between the two variables. In this case, using the line of best fit to make predictions may not be accurate.
Overall, the correlation coefficient can help us determine how well the line of best fit represents the data and how confident we can be in using it to make predictions.