# MAT 240 SNHU Real State Selling Price and Area Analysis

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 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.

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.
• 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 PDF 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?

You can use the following tutorial. Make sure to check the assignment prompt for specific numbers used for national statistics and/or square footage. The video may use different national statistics or solve for different square footage values.