MAT 240 Module Three Assignment - D

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Rasmussen College *

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240

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Economics

Date

Apr 3, 2024

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docx

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4

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Housing Price Prediction Model for D.M. Pan Real Estate Company Desiree McKenzie Southern New Hampshire University
Median Housing Price Prediction Model for D.M. Pan National Real Estate Company 2 Module Two Notes Real estate is a fast-paced industry in which data analysis can offer a competitive advantage in helping resourceful agencies stay ahead of the game. Although it is important for real estate agents to study the physical attributes of the properties they show, it is equally as important for them to have extended knowledge of those homes in order for them to understand the relationship between factors such as home price, square footage, location, age of the home, and comparable home values. The purpose of this report is to provide D.M Pan Real Estate Company with a method to help predict the business environment to provide the best service to their clients. To do this, I’ve created a random sample of 30 properties from a particular region and will be analyzing the relationship between the selling price of the properties and their square footage. Regression Equation 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000 5,500 6,000 $200,000 $250,000 $300,000 $350,000 $400,000 $450,000 $500,000 $550,000 $600,000 $650,000 $700,000 $750,000 $800,000 f(x) = 102.36 x + 160349.87 R² = 0.81 Real Estate Sample The sample data being presented is of 30 properties randomly selected from the Mountain region. For this particular region, the regression equation is y = 102.36x + 160350.
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