Question

on todays episode of science time with zane, zane demonstrates that walking speed affects how wet a person will get in the rain. he simulates walking through the rain at various speeds.
zane keeps track of his walking speed (in meters per second), x. next, he measures how wet he is by taking the difference of his weight before and after walking through the rain (in kilograms), y.
the correct least squares regression line for the data set is:
y = -1.538x + 2.487
use it to complete the following sentence:
the least squares regression line predicts that a 1 meter per second increase in walkin speed will cause a person to soak up fewer kilograms of water.

Explanation:

Step1: Recall the slope - intercept form of a linear equation

The equation of a line is \(y = mx + b\), where \(m\) is the slope and \(b\) is the \(y\) - intercept. In the regression line \(y=-1.538x + 2.487\), the coefficient of \(x\) is the slope.

Step2: Interpret the slope in the context of the problem

The slope \(m=-1.538\) represents the change in \(y\) (amount of water, in kilograms) for a unit change in \(x\) (walking speed, in meters per second).

Answer:

\(1.538\)