Predicting Housing Prices

Statistics · Axiom Academy

REAL WORLD Predicting Housing Prices How Zillow, Redfin, and real estate professionals use regression to estimate property values Imagine you're selling your home. You list it online, and within minutes, Zillow displays a "Zestimate" of 487,300. How did they calculate that number so quickly without even seeing inside your house? The answer: statistical regression . Real estate platforms analyze millions of data points from past home sales to predict prices. This same technique is used by: Zillow & Redfin - Automated home valuations (Zestimates) Real estate agents - Comparative Market Analysis (CMA) Banks & lenders - Mortgage approval decisions Property tax assessors - Annual tax valuations Let's explore how this works, starting with the simplest model. The Simplest Model: Square Footage The strongest predictor of home price is usually square footage . Let's start with a simple linear regression using just this one variable. Simple Linear Regression Model: Where: Price = intercept + (slope × square feet) Using only square footage gives us a rough estimate, but think about real homes you've seen... Question: Two houses both have 2,500 square feet. One is brand new in a great school district. The other is 40 years old next to a highway. Should they have the same predicted price? Multiple Regression: The Real-World Solution

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