MAT 240 Module Two Assignment
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Southern New Hampshire University *
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Apr 3, 2024
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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
Alexis Santos
Department of Mathematics, SNHU
MAT 240: Applied Statistics
Professor Andrew Maner
1/21/2024
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
Introduction
As the newest junior analyst at the D.M. Pan National Real Estate Company, I have been tasked with preparing an analytic report based off data from the Real Estate County Data spreadsheet from 2019. This report includes a representative sample of the data, an analysis of the sample, a scatterplot of the data and any observed patterns from the data sample. The purpose
of this report is to examine the relationship between the selling price of properties and their size in square feet. Representative Sample of the Data
The sample of the data that is being analyzed in this report is from the West South Central region and is data from the state of Texas. This report analyzes the data of 30 counties in the state and includes the listing price, cost per square foot, and square feet of real estate property
within the state. The mean of the listing price is $315,014 with a median price of $261,850. The standard deviation of the listing price is $146,932. The mean of the cost per square foot is $127 with a median price of $124. The standard deviation of the cost per square foot is $19. The mean of the square feet is 2,536 with a median of 2,000. The standard deviation of the square feet is 1,275.
Analysis of the Sample
The regional sample that was created of the data from the state of Texas is reflective of the national market through different aspects of each report. The mean and median listing prices of both reports are close in range to each other and reflect that both markets listing prices are similar in price. The standard deviation of the listing prices reports shows that the standard deviation of Texas is higher by $21,018. The cost per square foot of both reports reflect that the
Selling Price and Area Analysis for D.M. Pan National Real Estate Company
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national market is higher than the 30 counties from the state of Texas. The square feet of both reports show that the data of the regional sample is higher than the national market. This reflects that the square feet per real estate property in Texas is bigger than the national market. To truly get a random sample from the 2019 data spreadsheet I scanned through the data sheet and chose Texas to analyze because I was curious how Texas compared to the national market since it is such a big state. Scatter Plot
Observed Patterns
X is defined as an independent variable while y is the dependent variable. In this scatter plot, X is square feet and Y is the listing price from the 30 counties in Texas. In terms of which variable is useful for making predictions, X is the most useful. This is because X can be manipulated and changed while Y needs to be influenced by X.
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Selling Price and Area Analysis for D.M. Pan National Real Estate Company
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There can be an association between x and y. This association can be positive or negative or no correlation at all, depending on the direction of scatter plots. Inserting a trend line can also help determine if there is an association between x and y. In this scatterplot there is a positive association between x and y.
The shape of this scatterplot is moderate linear. This scatterplot does have a linear shape but also does have a nonlinear look towards the left side of the scatterplot. If there were a 1,800 square foot house for example, based on the regression equation of 109.94x+36,191, the listing price would be $234,083. In this scatterplot there may possibly be two outliers. These outliers appeared in this scatterplot because they appear to fall outside the average range of values and are an extreme value. These outliers represent a larger square foot property with a high listing price.