You’re a realtor with a client in the market for a 3+ bedroom home with at least 2 baths.  Randomly sample 10 homes from your original data set from Part A that meet these criteria

 

You’re a realtor with a client in the market for a 3+ bedroom home with at least 2 baths.  Randomly sample 10 homes from your original data set from Part A that meet these criteria.  Write a report that includes a linear regression model that predicts a home’s listing price based on its size (in square feet).  The use of EXCEL or other data software may be beneficial.

  1. Write an introduction that includes the context of the data and precisely describes the sampling method used to achieve your random sample. Provide a data table that includes the 10 selected homes, their square footage, and their listing price. Calculate the mean and standard deviation for both square footage and price.
  2. Create a scatterplot showing the association between the two variables. The scatterplot should include the least-squares line and a generic version of the regression equation.
  3. Describe the association’s direction and form in context of the variables. Describe the strength of the association by providing a calculated correlation coefficient.
  4. Provide a contextual version of the regression equation. Interpret the slope, intercept, and R2 of the model in context of the two variables.
  5. Note any outliers or influential points in your scatterplot. Describe what might happen to your model if they were excluded.
  6. Select one home from your list of 3+ bedroom, 2+ bathroom homes. Interpret the residual associated with this selection. Is the home a good deal, fair deal, or poor deal for your client?
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