AI engineering glossary · Statistics inference
What is homoscedasticity?
Homoscedasticity: The assumption that the spread of a regression model's errors is the same across all values of the predictors. When it holds, standard errors and tests from ordinary least squares are reliable.
Homoscedasticity: an example
Prediction errors for house prices are about Rs 2 lakh whether the house is cheap or expensive.
Related terms
More Statistics inference terms
- Instrumental variable
- Interaction term
- Jackknife
- Kolmogorov-Smirnov test
- Likelihood function
- Likelihood ratio test
- Log-likelihood
- Mann-Whitney U test
Where you learn it
Homoscedasticity is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.