Real Estate Data Spreadsheet Link: https://learn.snhu.edu/content/enforced/1754074-MAT-240-17462.202486-1/course_documents/MAT%20240%20Real%20Estate%20Data.xlsx?ou=1754074
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.
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.
1.) 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.
2.)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 PDF document.
- Explain how you have made sure that the sample is random.
- Explain your methods to get a truly random sample.
3.) Generate Scatterplot
- Create a scatterplot of the x and y variables noted above. Include a trend line and the regression equation. Label the axes.
4.) 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?