You have been hired by the D. M. Pan National Real Estate Company to develop a model to predict housing prices for homes sold in 2019. The CEO of D. M. Pan wants to use this information to help their real estate agents better determine the use of square footage as a benchmark for listing prices on homes. Your task is to provide a report predicting the housing prices based square footage. To use the provided real estate data set for all U.S. home sales as well as national descriptive statistics and graphs provided.

Describe the report: Give a brief description of the purpose of your report.

1. Define the question your report is trying to answer.
2. Explain when using linear regression is most appropriate.
   1. When using linear regression, what would you expect the scatterplot to look like?
3. Explain the difference between predictor (x) and response (y) variables in a linear regression to justify the selection of variables.
4. Interpret the graphs and statistics:
   1. Based on your graphs and sample statistics, interpret the center, spread, shape, and any unusual characteristic (outliers, gaps, etc.) for house sales and square footage.
   2. Compare and contrast the center, shape, spread, and any unusual characteristic for your sample of house sales with the national population (under Supporting Materials, see the National Summary Statistics and Graphs House Listing Price by Region PDF). Determine whether your sample is representative of national housing market sales.