MAT 240 M3-3
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Apr 3, 2024
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Dustin 1
Housing Price Prediction Model for D.M. Pan National Real Estate Company
Dustin Bowman
Department of Math, Southern New Hampshire University
MAT 240: Applied Statistics
Professor Konrath
January 27
th
2024
Housing Price Prediction Model for D.M. Pan National Real Estate Company
Dustin 2
Regression Equation Y= 88.1X + 71660
Determine R
R=.90 (.897189) R represents the correlation between the data points and the line of regression. It is a positive regression and has a strong correlation. Having a positive R value indicates that the slope is positive in nature and travels upward. An R value that is between .8 and 1 is interpreted as a strong correlation. As the X variable (Sq. Ft.) increases, so does the Y variable (Listing Price). Examine the Slope and Intercepts The slopes value is 88.1 and the intercepts value is 71660. This shows us that for every Sq. Ft. That a home increases in size, the price of the home would increase by $88.10. To find the value
Dustin 3
of only the land we would input 0 for x in the regression equation to show 0 sq. Ft. This would then give us the intercept value of 71660. Implying that the cost of the land would be $71660.
R-squared Coefficient The R-squared value is .8049481017. Rounding to .80, that concludes that 80% variation in the listing price of the home is explained by the variation in square feet. Conclusions To conclude, there is a direct correlation between the Sq. Ft. Of a home and its corresponding listing price. If a home has more square feet, the home will also have a higher listing price. Based on the information provided concerning the National average, the North East Central Region shows to have a lower value per square foot. Based on the median price and square foot of the National average, the cost per square foot is $169.06, while the NWC Region sample I used places the value of a square foot at $131.42. When looking at the values provided from the National average and the values from my sample, we can conclude that the NWC Regions mean, median and standard deviation are significantly lower than the National averages while comparing the listing price and the square feet of the homes. Based on the regression equation we could use that to determine a viable listing price for a home based solely on the square footage. The slope can help identify price changes. The best square footage ranges the graph would be used for 500 to 4000 sq. Ft.
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