select a region, complete an initial analysis, and provide the report to the team.

Note: In the report you prepare for the sales team, the response variable (y) should be the listing price and the predictor variable (x) should be the square feet.

• Generate a Representative Sample of the Data
  • Select a region and generate a simple random sample of 30 from the data.
  • Report the mean, median, and standard deviation of the listing price and the square foot variables.
• Analyze Your Sample
  • Discuss how the regional sample created is or is not reflective of the national market.
    • Compare and contrast your sample with the population using the National Summary Statistics and Graphs Real Estate Data PDFdocument.
  • Explain how you have made sure that the sample is random.
    • Explain your methods to get a truly random sample.
• Generate Scatterplot
  • Create a scatterplot of the x and y variables noted above. Include a trend line and the regression equation. Label the axes.
• Observe patterns
  • Answer the following questions based on the scatterplot:
    • Define x and y. Which variable is useful for making predictions?
    • Is there an association between x and y? Describe the association you see in the scatter plot.
    • What do you see as the shape (linear or nonlinear)?
    • If you had a 1,800 square foot house, based on the regression equation in the graph, what price would you choose to list at?
    • Do you see any potential outliers in the scatterplot?
      • Why do you think the outliers appeared in the scatterplot you generated?
      • What do they represent?

https://www.dropbox.com/scl/fi/qb0sjjovf20l1vui86j4t/MAT-240-Real-Estate-Data.xlsx?rlkey=0nxq8q4x949nnyr1o6bsznl7o&dl=0