Question

question 21 of 27
interpret the value of s.
the actual free skate score is typically about 10.2 points away from the score predicted by the least - squares regression line with x = short program score.
the actual free skate score is typically about 10.2 points lower than the score predicted by the least - squares regression line with x = short program score.
the actual free skate score is typically about 10.2 points higher than the score predicted by the least - squares regression line with x = short program score.
for every 1 point increase in the short program score, the predicted free skate score increases by 10.2 points.
10.2% of the variation in free skate score is accounted for by the least - squares regression line with x = short program score.

Explanation:

In regression analysis, the standard error of the estimate ($s$) represents the average amount by which the observed values deviate from the predicted values. It is not a measure of whether the actual values are higher or lower on average, nor is it a slope - related measure (as in the case of the change in predicted value per unit change in the independent variable). Also, it is not a measure of the proportion of variance accounted for (that's $R^{2}$). So, the actual value is typically the standard error amount away from the predicted value.

Answer:

The actual free skate score is typically about 10.2 points away from the score predicted by the least - squares regression line with $x =$ short program score.