R-squared is the percent of price variation in our dataset that is captured by the model. It is a percent from 0-100%. A high R-squared means that the model did a good job at explaining the variation between properties. A low R-squared means that the model couldn’t capture a lot of the reasons that there are price differences among homes in the area. The appraiser should rely on his area expertise to consider additional adjustments.
Articles in this section
- FAQ Regression - What does R squared signify?
- FAQ Regression - How can bedrooms be considered an insignificant attribute?
- FAQ Regression - What is collinearity? Why is it important?
- FAQ Regression - Do appraisers have to use the regression results?
- FAQ Regression - Can I make an adjustment even when an attribute is not considered significant?
- FAQ Regression - What’s the value of analyzing 2000 properties? Don't we just need three?
- FAQ Regression - What does significant mean?
- FAQ Regression - When should I make adjustments to attributes other than the ones HouseCanary analyzed?
- FAQ Regression - What do the sliders mean?