MAT 240 Module Three Assignment
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Apr 3, 2024
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Housing Price Prediction Model for D.M. Pan National Real Estate Company
Leslie R. Rossner
Department of Mathematics, SNHU
MAT 240: Applied Statistics
Professor Jennifer Turner
January 28, 2024
2
Housing Price Prediction Model for D.M. Pan National Real Estate Company
Module Two Notes
The correlation of selling prices in real estate and the square footage of the property is what is being explored in this report. This report analysis will be providing insight to D.M. Pan National Real Estate Company by analyzing the provided national average statistics and thirty randomly selected houses in the East North Central region. This report will provide the company with comprehension between these aspects of real estate. Generate a Representative Sample of the Data
EAST NORTH CENTRAL LISTING PRICE
MEDIAN
$343,350
MEAN
$359,768
STANDARD DEVIATION
$130,495
EAST NORTH CENTRAL SQUARE FOOTAGE
MEDIAN
1,890
MEAN
2,147
STANDARD DEVIATION
901.15
NATIONAL AVERAGE
Listing Price
Square Footage
MEDIAN
318,000
1,881
MEAN
342,365
2,111
STANDARD DEVIATION
125,914
921
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Regression Equation
The equation used to determine the regression for listing price and square footage is
y = 119.4x + 103392 where x = Square Feet (SqFt)
Determine r
The association between the listing price and square footage is represented by the r value.
In this case, the R value is 0.68. Examine the Slope and Intercepts
In this sample the 119.4 is determined to be the slope and the intercept is 103392. When there is a change in listing price and square footage, that is what the slope is representing. In other words, the price increases by $119.40 for every square foot. Considering the intercept represents zero square feet, it is not accurate to determine the price for an empty plot of land with
no information. R-squared Coefficient
The correlation between the two variables is a strong correlation as the coefficient is 0.679859 and is between 0 and 1. This indicates that 68% (rounded) of listing price variations can be associated to the square footage. Conclusions
It is concluded that the correlation between variables is strong and positive which amounts to when price increases so does the square footage and vice-versa. It is safe to conclude that square footage can be used to predict listing price for this region.
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