Question

A county real estate appraiser wants to develop a statistical model to predict the appraised value of houses in a section of the county called East Meadow. One of the many variables thought to be an important predictor of appraised value is the number of rooms in the house. Consequently, the appraiser decided to fit the linear regression model E(y)= Bo +P1x, where y equals the appraised value of the house in thousands of dollars) and X equals the number of rooms. Using data collected for a sample of n = 74 houses in East Meadow, the following result was obtained. y = 74.80 + 23.71x Give a practical interpretation of the estimate of the slope of the least squares line.

Answer 1

Answer: D

Explaination

slope is coefficient in front of x thus slope is 23.71

slope = Rise/Run hence we can write it as fraction 23.71/1.Rise is change in y for every single value change in x

we can write it as for each additional room in the house, we estimate the appraised value to increase $ 23,710