# QNT/351 Version 5 Real Estate Regression Exercise

Real Estate Regression Exercise
QNT/351 Version 5 University of Phoenix Material
Real Estate Regression Exercise
Directions: Use the real estate data you used for your Week 2 learning team
You are consulting for a large real estate firm. You have been asked to construct a model that can predict
listing prices based on square footages for homes in the city you’ve been researching. You have
data on square footages and listing prices for 100 homes.
1. Which variable is the independent variable (x) and which is the dependent variable (y)?
The sold price is the independent variable X and the square footage is the dependent Y varialble 2. Click on any cell. Click on Insert→Scatter→Scatter with markers (upper left).
To add a trendline, click Tools→Layout→Trendline→Linear Trendline
Does the scatterplot indicate observable correlation? If so, does it seem to be strong or weak?
In what direction?
Yes there is a strong correlation with an increase in price there is also an increase in square
footage. The line has a positive slope.
headings) and input the correct columns into Input Y Range and Input X Range, respectively.
Make sure to check the box entitled “Labels”.
(a) What is the Coefficient of Correlation between square footage and listing price? Regression Statistics
Multiple R
0.814503773
R Square
0.663416397