2-3 Assignment Real Estate Analysis Part I

.docx

School

Southern New Hampshire University *

*We aren’t endorsed by this school

Course

240

Subject

Mathematics

Date

Apr 3, 2024

Type

docx

Pages

Uploaded by BrigadierResolve10210

Report: Selling Price and Area Analysis for D.M. Pan National Real Estate Company DiAngeles Lino Department of Mathematics, SNHU MAT 240: Applied Statics Matthew Elwer January 15,2024

Introduction This research aims to give D.M. Pan National Real Estate Company a competitive edge in home sales by offering an intuitive analysis. Real estate brokers must also understand how pricing, square footage, build year, location, and many other variables relate to one another to forecast the business climate and give their customers the best counsel. This report's investigation of the connection between a property's square footage and selling price is one of its other goals. I was given a Real Estate County Data sheet, which also included data on homes that had recently been sold across the country. Representative Data Sample The East North Central region is the one I have selected for my basic random sample of thirty. The median listing price has the following mean, median, and standard deviation: mean $221.526, median $179,863, and standard deviation 110713.303. The variables related to median square foot have the following mean, median, and standard deviation: 1955, 1769, and 520.347231, respectively. Data Analysis The developed East North Central regional sample is not a good reflection of the country's population and is not indicative of the national market. Using the National data and Graphs document, I compared my regional sample with the national population. The mean listing price for my sample is $221,526 while the mean listing price for the national data is $288,419. The national statistics and graphs show that the median is $256,936, yet the median from my random sample is $179,863. The national statistics and graphs papers' standard deviation is 163,986, while the standard deviation from my random sample is 110713.303. I calculated the standard deviation in Excel using the formula =STDEV.S(D2:D31) to ensure that the sample was indeed random. The Pattern

The median square footage (x) and median listing price (y) in my graph are based on observations. It is accurate to anticipate the median listing price based on square footage. X and Y are related, and the connection is a positive liner. A 12,000 square foot property would be my choice to market at $92,356, according to the graph's regression equation. Based on the available data, I would opt to sell a 12,000 square foot house for $92,356, as it is the average listing price for a house of that size in a neighborhood that is like the locations of the other units on the listing that also have that size. The scatterplot's relationship between x and y shows that the median listing price grows in proportion to the median square footage and has a linear form. Three outliers stand out to me in the graph. Examples of these include the counties, school districts, and the desirability of the neighborhood where the residences are located. The outlines show values that are out of the ordinary for the set of data.

Your preview ends here

Eager to read complete document? Join bartleby learn and gain access to the full version

Access to all documents
Unlimited textbook solutions
24/7 expert homework help