# Directions Use the real estate datayou used for your Week 2

Directions: Use the real estate datayou used for your Week 2 learning team assignment. Analyze the data and explain your answers.  Youare consulting for a large real estate firm. You have been asked to construct a model that can predict listing pricesbased on square footages for homes in the city you’ve been researching.  You have data on square footages and listingprices for 100 homes.1.   Which variable is the independent variable (x)and which is the dependent variable (y)? 2. Click on any cell.  Click on Insert→Scatter→Scatter with markers(upper left).To add a trendline, clickTools→Layout→Trendline→Linear TrendlineDoes thescatterplot indicate observable correlation? If so, does it seem to be strong or weak?     In what direction?3. Click on Data→Data Analysis→Regression→OK.  Highlight your data (including your twoheadings) and input the correct columns into Input Y Range and Input X Range,respectively.  Make sure to check the boxentitled “Labels”.  (a)  Whatis the Coefficient of Correlation between square footage and listingprice?  (b)  Doesyour Coefficient of Correlation seem consistent with your answer to #2above?  Why or why not?  (c)  Whatproportion of the variation in listing price is determined by variation in thesquare footage?  What proportion of thevariation in listing price is due to other factors?(d)  Checkthe coefficients in your summary output. What is the regression equationrelating square footage to listing price?(e)  Testthe significance of the slope. What is your t-value for the slope?  Do you conclude that there is no significantrelationship between the two variables or do you conclude that there is asignificant relationship between the variables?(f)  Usingthe regression equation that you designated in #3(d) above, what is thepredicted sales price for a house of 2100 square feet?

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Cathy, CS.