No, you cannot be confident that your predicted value will be reasonably close to the actual value. A correlation coefficient of -0.833 indicates a strong negative linear relationship between the variables in the data set. However, it does not guarantee that the predicted value will be close to the actual value. The line of best fit represents the average relationship between the variables and does not account for possible outliers or other factors that may affect the accuracy of the prediction.
Additionally, the accuracy of the prediction also depends on the variability of the data and the goodness of fit of the regression model. If the data points are spread out and do not closely follow a linear trend, the predicted value may deviate further from the actual value. Furthermore, the regression model assumes that the relationship between the variables is linear and does not consider any non-linear relationships between them. Therefore, even with a strong negative linear relationship, there could be other nonlinear patterns or relationships that are not captured by the model, leading to a less accurate prediction.
