Housing Price Prediction Model for D.M. Pan Real Estate Company

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
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Chapter1: Starting With Matlab
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Housing Price Prediction Model for D.M. Pan Real Estate Company

Southern New Hampshire University

 

Module Two Notes

 

I chose a random sample of 30 by using the rand(). I then chose the first 30 random variables.

 

 

Regression Equation

y = 98.771x + 140766

Determine r

 R= 0.73116624 which means that the variables are related to eachother. There is no practical interpretation between the two variables because no one would pay $140,766 for 0 sq. footage.  

Examine the Slope and Intercepts

The slope is 98.771 and intercept is 140766. The x variable (sq footage) is independent, listing price, (or Y) is dependent. The slope is interpreted as the change in listing price for a one unit increase in square footage. So, as the square footage increases, the listing price increases by 98.771. The intercept shows when X is 0, Y is $140,766. By assuming the square foot as 1192, the cost or value of land comes out to be $258,501.

R-squared Coefficient

R^2 measures the variation in the listing price that can be explained by the variation in the square footage meaning that value of . 0.53460408 would be 53%.

Conclusions

NEED HELP ON THIS PART*****[Reflect on the relationship between square feet and sales price by addressing key considerations such as the comparison between your selected region and overall homes in the United States, as well as analyzing how the slope can help identify price changes, how the regression equation can help identify appropriate listing prices, and what square footage ranges the graph would be best used for.]

Relationship between square feet and sales price is that as the square footage increases, the listing price increases by $98.771. The intercept shows when X is 0, Y is $140,766. There is no practical interpretation between the two variables because no one would pay $140,766 for 0 sq. footage.  The slope is interpreted as the change in listing price for a one unit increase in square footage. So, as the square footage increases by one, the listing price increases by 98.771. The intercept shows when X is 0, Y is $140,766. By assuming the square foot as 1192, the cost or value of land comes out to be $258,501.

 

 

 

 

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