Question

Acreage and Value. The data from Exercise 4.73 for lot size (in acres) and assessed value (in thousands of dollars) for a sample of homes in a particular area are on the WeissStats site.

Short answer

a). The linear correlation coefficient was chosen because it provides a descriptive measure of data.

b). The linear correlation coefficient is left out of the equation.

c). There is no calculation of the linear correlation coefficient.

Step-by-step solution

Part (a) Step 1: Given Information

The table below shows the lot size and assessed value for a sample of residences in a certain location.

Part (a) Step 2: Explanation

Draw a scatter plot showing the relationship between lot size and assessed value for a sample of properties in a certain location.

The scatter plot shows that the data points are distributed non-linearly.

As a result, the linear correlation coefficient, which is not a descriptive data metric, is used. As a result, parts b and c have been left out.

Part (b) Step 1: Given Information

The table below shows the lot size and assessed value for a sample of residences in a certain location.

Part (b) Step 2: Explanation

Component a provides the scatter plot for lot size and assessed value for a sample of dwellings in a certain location.

The scatter plot shows that the data points are distributed nonlinearly.

As a result, the linear correlation coefficient, which is not a descriptive data metric, is used.

As a result, the linear correlation coefficient is omitted from the equation.

Part (c) Step 1: Given Information

The table below shows the lot size and assessed value for a sample of residences in a certain location.

Part (c) Step 2: Explanation

Using the data from section a, we must build a scatter plot for lot size and assessed value for a sample of dwellings in a specific region.

After looking at the scatter plot, we decided to use the linear correlation coefficient. A descriptive measure of data is not the linear correlation coefficient.

As a result, there is no calculation of the linear correlation coefficient.