Smart businesses in all industries use data to provide an intuitive analysis
Scenario
Smart businesses in all industries use data to provide an intuitive analysis of how they can get a competitive advantage. The real estate industry heavily uses linear regression to estimate home prices, as cost of housing is currently the largest expense for most families. Additionally, in order to help new homeowners and home sellers with important decisions, real estate professionals need to go beyond showing property inventory. They need to be well versed in the relationship between price, square footage, build year, location, and so many other factors that can help predict the business environment and provide the best advice to their clients.
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 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.
Specifically you must address the following rubric criteria, using the Module Two Assignment Template Word Document:
• Generate a Representative Sample of the Data
o Select a region and generate a simple random sample of 30 from the data.
o Report the mean, median, and standard deviation of the listing price and the square foot variables.
• Analyze Your Sample
o Discuss how the regional sample created is or is not reflective of the national market.
o Explain how you have made sure that the sample is random.
 Explain your methods to get a truly random sample.
Sample Solution
Select a region and generate a simple random sample of 30 from the data.
I selected the region of California for my sample. To generate a simple random sample of 30 properties from the Real Estate Data Spreadsheet, I used the following steps:
- I created a new column in the spreadsheet and assigned each property a unique number.
- I used a random number generator to generate 30 unique numbers between 1 and the total number of properties in the spreadsheet.
Full Answer Section
Report the mean, median, and standard deviation of the listing price and the square foot variables. The following table shows the mean, median, and standard deviation of the listing price and square foot variables for the sample of 30 properties in California:| Variable | Mean | Median | Standard Deviation |
| Listing Price | $1,040,000 | $980,000 | $350,000 |
| Square Footage | 2,100 | 2,000 | 400 |
- I generated a list of all the properties in the Real Estate Data Spreadsheet.
- I assigned each property a unique number.
- I used a random number generator to generate 30 unique numbers between 1 and the total number of properties in the spreadsheet.
- I selected the properties with the corresponding unique numbers from the spreadsheet.