Question

read the following description of a data set.
a professor wants to know if a students first exam score can be used to accurately predict his or her final exam score.
he looked at how some of his previous students did on their first exam, x. he also looked at their final exam scores, y. both exams were graded out of 100.
the least squares regression line of this data set is:
y = 0.299x + 53.426
complete the following sentence:
the least squares regression line predicts that if a student got an additional point on the first exam, their final exam score would be points higher.

Explanation:

Step1: Recall the regression line formula

The regression line is \(y = mx + b\), where \(m\) is the slope.

Step2: Interpret the slope

In the equation \(y = 0.299x + 53.426\), the slope \(m = 0.299\). The slope represents the change in \(y\) (final exam score) for a unit change in \(x\) (first - exam score).

Answer:

\(0.299\)