What Drives Home Values in Ames, Iowa?

Ahmed Elsaeyed

Building Our Predictive Model

To identify the key drivers of home values, we built a multiple linear regression model using the most influential features.

Metric Value
R-squared 80.8%
Adjusted R-squared 80.7%
Mean Absolute Error $21,655.09
Root Mean Squared Error $34,819.79

Our model explains 80.8% of the variation in housing prices using these key features.

Understanding the Model Coefficients

The model coefficients tell us exactly how much each feature impacts the home price, all else being equal.

How Well Does the Model Fit?

Our model does a good job of predicting home prices, but let’s examine how it performs across different price ranges.

What’s the Formula for Home Value?

The true value of our model is in understanding the relative importance of features.

Here’s what standardized coefficients tell us about what really drives home prices:

Analysis of Home Size

Quality Makes a Big Difference

A home’s overall quality rating is the single most consistent predictor of its price.

Quality vs. Price per Square Foot

Location is Critical

Despite quality and size being major factors, location continues to be a fundamental driver of home values.

Hidden Value Drivers

Home Age and Condition

Newer homes tend to command a premium. Homes built in the 2000s typically sell for $20,000 more than similar homes from the 1920s.

Improvements with the Biggest ROI

If you’re looking to increase your home’s value, kitchen upgrades and overall quality improvements give you the best bang for your buck.