MAT 240 Module Two Assignment Template
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Southern New Hampshire University *
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240
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Mathematics
Date
Feb 20, 2024
Type
docx
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3
Uploaded by GrandLeopard2382
Selling Price and Area Analysis for D.M. Pan National Real Estate Company
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Report: Selling Price and Area Analysis for D.M. Pan National Real Estate Company
Nikiya Bailey
Department of Mathematics, SNHU
MAT 240: Applied Statistics
Pro. Sally Worrell Nichols
01-21-2024
Selling Price and Area Analysis for D.M. Pan National Real Estate Company
2
Report: Selling Price and Area Analysis for D.M. Pan National Real Estate Company
Introduction
Hello everyone, I am here today to provide intuitive analysis of how people can get a competitive advantage. Today I will be presenting Data of the South Atlantic Region. Now a days housing is the most thing that people must pay for. And it is very important that we help them in every way that we can. Price, location, square footage, build year, and so many other factors that can help predict the business environment and provide the best advice to their clients.
Generate a Representative Sample of the Data
I did a simple random sample of 30 houses from the South Atlantic region which are 3 different states which are North Carolina, South Carolina, and Georgia. First, I will identify the mean of the listing price which is 367164.5161. The median is 362900 for the listing price. And the standard deviation is 52130.31459 of listing price. The mean for square footage is 362900. The median for square footage is 2107. And the standard deviation for square footage is 259.4095985. Analyze Your Sample
The regional sample that I created I also compared it to the National Statistics and Graphs; you can see how things have increased. As you can see, we both compared numbers the same way to get the data that we received, but things now a days are higher, and of course in different regions the cost of living is higher, and people make more money too in these areas. I made sure that when I picked a region, I randomly selected 30 to make sure that it was random, I did not look at the numbers when picking to ensure that it would be random on what I was picking. The only thing that was not random was the region because I was curious about how much the price would be in that specific area.
Selling Price and Area Analysis for D.M. Pan National Real Estate Company
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Generate Scatterplot
Observe Patterns
X is square footage, and Y is the Listings price. X is the variable that is useful for making
predictions. There is an association between x and y because they are so close together. The scatterplot is strong because it is in a cluster, and positive. It is also a linear line. If I had a 1800 square foot house, based on the regression equation in the graph the price would list at $375,395.40. There are no potential outliners in the scatterplot.
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