Standard Error of the Estimate

Answers

1. The standard error of the estimate is a measure of the accuracy of predictions. The regression line is the line that minimizes the sum of squared deviations of prediction (also called the sum of squares error), and the standard error of the estimate is the square root of the average squared deviation.
   
   
2. The standard error of the estimate for a population = sqrt[(1-rho²)*SSY/N] = sqrt[(1-.5²)*50/100] = .61
   
   
3. The standard error of the estimate for a sample = sqrt[SSE/(N-2)] = sqrt[5.8/8] = .85
   
   
4. The standard error of the estimate for a sample = sqrt[SSE/(N-2)]. SSE is the sum of the squared errors of prediction, so SSE = (-.2)² + (.4)² + (-.8)² + (1.3)² + (-.7)² = 3.02; sqrt(3.02/3) = 1.0