You have been recently hired as a junior analyst by D.M. Pan Real Estate Company

Prompt

  • You have been recently hired as a junior analyst by D.M. Pan Real Estate Company. The sales team has tasked you with preparing a report that examines the relationship between the selling price of properties and their size in square feet. You have been provided with a Real Estate Data spreadsheet that includes properties sold nationwide in recent years. The team has asked you to select a region, complete an initial analysis, and provide the report to the team.
  • 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 document.
    • 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 and include a trend line and the regression equation
  • 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?
          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.

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