MAT 240 Project One Template

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Southern New Hampshire University *

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MAT240

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Economics

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Apr 3, 2024

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docx

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7

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Median Housing Price Prediction Model for D. M. Pan National Real Estate Company 1 Report: Housing Price Prediction Model for D. M. Pan National Real Estate Company Shaterria Johnson Southern New Hampshire University
Median Housing Price Model for D. M. Pan National Real Estate Company 2 Introduction I have been hired by D.M. Pan National Real Estate Company to provide a report to see if the housing prices based on square footage are appropriate. This will help real estate agents determine if square footage should be a benchmark for home listing prices. Using Linear regression is only appropriate if the relationship between the predictor variable (square footage) and the response variable(housing listing price) is linear. The response variable must be a continuous numeric variable. When using linear regression, I would expect the scatterplot to look like an upward continuous positive slope. The response variable is a random variable, while the predictor variable is assumed to be non- random or fixed and measured without error. The relationship between the response and predictor variables must be linear, given by the model y ^ = b 0 + b 1 x2. Data Collection I selected a random sample of 50 by first using the Excel function on the data spreadsheet =rand() for all houses listed. After successfully randomizing the houses, I sorted the list from smallest to largest and chose the first 50 houses listed. My predictor variable is the median square foot of the house and my response variable is the housing listing price.
Median Housing Price Model for D. M. Pan National Real Estate Company 3 - 1,000 2,000 3,000 4,000 5,000 6,000 - 100,000 200,000 300,000 400,000 500,000 600,000 700,000 800,000 900,000 Real Estate County Data 2019 Random Sample Square footage Median House listing price Data Analysis
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