Question

A statistics teacher was interested in the relationship between the number of days students waited to start a project and the score that project received (out of 100 points). Information was collected on several students and was used to obtain the regression equation ŷ = –3.64x + 96.5, where x represents the number of procrastination days and ŷ is the predicted grade. Which statement best describes the meaning of the slope of the regression line?

A:For each increase in number of procrastination days by 1, the predicted grade decreases by 3.64 points.
B;For each increase in number of procrastination days by 1, the predicted grade decreases by 96.5 points.
C;For each increase in grade by 1 point, the predicted number of procrastination days decreases by 96.5 days.
D:For each increase in grade by 1 point, the predicted number of procrastination days decreases by 3.64 days.

Answer 1

Pretty sure the guy above me is right, although I have not checked on edge.

(A) For each increase in number of procrastination days by 1, the predicted grade decreases by 3.64 points.

kinda sucks how theres nothing for stats on here but i hope to help a little =================================

if you're looking for "What is the predicted grade of a student who procrastinated for 2 days?" as-well, the answer for that seperate question is (C) 89.22 .

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ED2021

Answer 2

A: For each increase in the number of procrastination days by 1, the predicted grade decreases by 3.64 points.

Explanation:

The slope of a Regression Line

A straight line can be represented in the slope-intercept form:

y = mx + b

Where m is the slope and b is the y-intercept.

The slope describes how fast and in what direction the graph goes when x changes values.

If m is positive, increments in x imply increments in y.

If m is negative, increments in x imply decrements in y.

The regression line is:

ŷ = –3.64x + 96.5

Where:

x = the number of procrastination days

ŷ = the predicted grade

We can say the slope is m=-3.64. This means that:

A: For each increase in the number of procrastination days by 1, the predicted grade decreases by 3.64 points.