Determining the selling price of a home

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Reference no: EM132654838

Determining the Selling Price of a Home Determining how much to pay for a home is one of the more difficult decisions that must be made when purchasing a home. There are many factors that play a role in a home's value. Location, size, number of bedrooms, number of bathrooms, lot size, and building materials are just a few. Fortunately, the website Zillow.com has developed its own formula for predicting the selling price of a home. This information is a great tool for predicting the actual sale price. For example, the data to the right show the "zestimate"-the selling price of a home as predicted by the folks at Zillow and the actual selling price of the home for homes in Oak Park, Illinois.

The graph below, called a scatter diagram, shows the points (291.5, 268), (320, 305), . . . , (368, 385) in a Cartesian plane. From the graph, it appears that the data follow a linear relation.

1. Imagine drawing a line through the data that appears to fit the data well. Do you believe the slope of the line would be positive, negative, or close to zero? Why?

2. Pick two points from the scatter diagram. Treat the zestimate as the value of x and treat the sale price as the corresponding value of y. Find the equation of the line through the two points you selected.

3. Interpret the slope of the line.

4. Use your equation to predict the selling price of a home whose zestimate is $335,000.

5. Do you believe it would be a good idea to use the equation you found in part 2 if the zestimate is $950,000? Why or why not?

6. Choose a location in which you would like to live. Go to www.zillow.com and randomly select at least ten homes that have recently sold.

(a) Draw a scatter diagram of your data.

(b) Select two points from the scatter diagram and find the equation of the line through the points.

(c) Interpret the slope.

(d) Find a home from the Zillow website that interests you under the "Make Me Move" option for which a zestimate is available.

Use your equation to predict the sale price based on the zestimate.

Reference no: EM132654838

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