Question

question 17 of 27 > the relationship between x = height of a student (in inches) and y = number of steps required to walk the length of a school hallway, is summarized with the regression line ŷ = 113.6 - 0.921x. for this model, technology gives s = 3.50 and r² = 0.399. interpret the value of s. the number predicted by the least - squares regression line is typically about 3.50 away from the actual number of strides required to walk the length of a school hallway with x = height of a student (in inches). the actual number of strides required to walk the length of a school hallway is always about 3.50 away from the number predicted by the least - squares regression line with x = height of a student (in inches). the actual number of strides required to walk the length of a school hallway is typically about 3.50 more than the number predicted by the least - squares regression line with x = height of a student (in inches). the actual number of strides required to walk the length of a school hallway is typically about 3.50 less than the number predicted by the least - squares regression line with x = height of a student (in inches). the actual number of strides required to walk the length of a school hallway is typically about 3.50 units away from the number predicted by the least - squares regression line with x = height of a student (in inches).

Explanation:

In regression analysis, the standard error of the estimate ($s$) represents the average distance that the observed values fall from the regression line. Here, $s = 3.50$ means that the number predicted by the least - squares regression line is typically about 3.50 away from the actual number of strides required to walk the length of a school hallway with $x$ being the height of a student.

Answer:

The number predicted by the least - squares regression line is typically about 3.50 away from the actual number of strides required to walk the length of a school hallway with $x$ = height of a student (in inches).