Chapter 26, Problem 26.16CYS

To determine

The equation of the least-square regression line for predicting selling price from appraised value.

Answer to Problem 26.16CYS

The correct option is Option (b), $\text{Price}=111.9+1.2103\times \text{appraised value}$.

Explanation of Solution

Given info:

The equation of the least square regression for predicting selling price from appraised value is given.

Reason for the correct answer:

From the Minitab output, the value of intercept of regression coefficient $\alpha$ is 111.9 and the value of the slope $\beta$ is 1.2103.

Substitute 111.9 for $\alpha$,

Thus, the equation of the least-square regression line is $\text{Price}=111.9+1.2103\times \text{appraised value}$.

Reason for the incorrect answers:

Option (a) $\text{Price}=1.2103+111.9\times \text{appraised value}$

From Minitab output, the equation of the least-square regression line for predicting selling price from appraised value is $\text{Price}=111.9+1.2103\times \text{appraised value}$.

Thus, the equation $\text{Price}=1.2103+111.9\times \text{appraised value}$ is incorrect.

Option (c) $\text{Price}=123.2+0.1540\times \text{appraised value}$.

From Minitab output, the equation of the least-square regression line for predicting selling price from appraised value is $\text{Price}=111.9+1.2103\times \text{appraised value}$.

Thus, the equation $\text{Price}=123.2+0.1540\times \text{appraised value}$ is incorrect.

Thus, option (a) and (c) are incorrect.

Conclusion:

Thus, the equation of the least-square regression line for predicting selling price from appraised value is $\text{Price}=111.9+1.2103\times \text{appraised value}$.

Statistics Concept Introduction

The equation of least-square line is,

$Y=\alpha +\beta X$

Where, Y denotes the Price, $\alpha$ denotes the intercept of regression coefficient and $\beta$ denotes the slope.