Analyzing Selling Prices and Square Footage in Real Estate
School
Southern New Hampshire University**We aren't endorsed by this school
Course
MAT 240
Subject
Mathematics
Date
Dec 11, 2024
Pages
3
Uploaded by ChefDragonMaster1212
Selling Price and Area Analysis for D.M. Pan National Real Estate Company1Report: Selling Price and Area Analysis for D.M. Pan National Real Estate CompanyKaitlyn Renee CaldwellDepartment of Mathematics, SNHUMAT 240: Applied StatisticsMs. Harris11/10/2024
Selling Price and Area Analysis for D.M. Pan National Real Estate Company2Report: Selling Price and Area Analysis for D.M. Pan National Real Estate CompanyIntroductionIn this report I analyzed the East North Central housing market and the National average and compared the two. I considered the square footage, the listing price, and the location of the homes to determine how the prices (listing price and the dollar amount per square foot) were determined. After determining the elements considered to create prices, I then compared it to the national average and created a scatter graft to compare. Generate a Representative Sample of the DataIf you look at the attachment attached to this report, you will see the 30 homes located in East North Central America that I chose for my sample. I discovered the mean median and the standard deviation of the listing price and the square foot variables. The mean of the listing price for these 30 homes is $229,707, the median of the listing price is $205,650 and the standard deviation of the listing price is 79,219. The square footage mean of the 30 homes in the sample is1,867, the median of the square footage for the 30 homes in the sample is 1,655 and the standard deviation is 800. Analyze Your SampleThe biggest difference in the sample and the national average is the listing price. The sample has an average of $229,707 where the National housing market average listing price is $342,365. Clearly the National average is greater than the samples given. The homes are also larger in the National housing market. The average square footage for a home from the sample given is 1,867 and the National housing market average square footage is 2,111. The sample wasmost likely taken years ago as prices have drastically increased. While determining the mean, median, and standard deviation I had to randomly pick a total of 30 homes to use for my sample.
Selling Price and Area Analysis for D.M. Pan National Real Estate Company3I used the chart provided and in the following collum I labeled it as random and had the document generate random numbers in that collum for all the East North Central homes. Then I had the document organize the list in order from least to greatest. I then used the top 30 homes on the chart since they are now in random order based off the number the document generated.Generate ScatterplotThe scatterplot chart is on the attachment included on this assignment. The regression equation is y= 90.918x +61292. Observe PatternsI was able to determine the listing price was a direct result of the square footage. If there was more square footage in a home, then the listing price would be higher so by that I determined the X axis would be the square footage and the Y axis would be the listing price. The scatterplot shows a relationship between the x and y axis as the x axis increases so does the y axis. It is a linear line graph with a steep incline. Based on the regression equation if a house had 1,800 square feet the listing price for thathome would be $223,648. There was a few potential outlier points that appeared in this scatterplot but the one that stuck out the most was point (3,581 , 461,400) which is a house with 3,581 square feet and was listed on the market for $461,400 in the Douglas county of Wisconsin. There are outlier points in the scatterplot because these samples were taken randomly. If the samples were taken in order by listing price or by square footage, the points on the scatterplotwould line up more on the linear line graph and there would be fewer potential outlier points. There would still be some since location also plays a role in the listing price.