You use a line of best fit for a set of data to make a prediction about an unknown value. The correlation coefficient for your data set is 0.984. How confident can you be that your predicted value will be reasonably close to the actual value?
The correlation coefficient, or r-value, measures the strength and direction of the linear relationship between two variables. It ranges between -1 and 1, where 1 indicates a perfect positive correlation, -1 indicates a perfect negative correlation, and 0 indicates no linear correlation.
In this case, the correlation coefficient is 0.984, which is very close to 1. This suggests a strong positive linear relationship between the variables. Therefore, you can be reasonably confident that your predicted value will be reasonably close to the actual value. However, it is important to note that the correlation coefficient only measures the strength and direction of the linear relationship, and does not guarantee the accuracy of the prediction. Other factors, such as the scatter of the data points around the line of best fit, outliers, and the appropriateness of the linear model, should also be considered when assessing the confidence of the prediction.