Question

Interpreting Simple Linear Regression

1. Linear correlation coefficient r = 0.794556
2. Coefficient of Determination ( r square) 0.631319
3. Standard Error of the estimate = 12.9668
4. SSR (Explained variation) = 5182.41
5. SSE ( Unexplained variation) = 3026.49
6. Total variation (SST) = 8208.90
7. Predicted equation or equation of the regression line (Y predicted or hat) = 0725983X + 16.5523
8. Level of Significance = 0.1
9. Critical Value= 0.378419

QuestionWhich number measures the distances from the prediction line to the actual values?

Answer 1

The distances from the prediction line to the actual values can be measured using the standard error of the estimate.

Step-by-step explanation:

The distances from the prediction line to the actual values can be measured using the standard error of the estimate. In this case, the standard error of the estimate is 12.9668. This value represents the average distance between the predicted values generated by the regression line and the actual values in the dataset. It is a measure of how well the regression line fits the data points.