Heteroskedasticity
Also called: heteroscedasticity, non-constant variance, robust standard errors
Heteroskedasticity means the variance of the errors is not constant across observations — spending varies more among high earners, volatility varies across market regimes. It doesn't bias OLS coefficients, but it wrecks the standard errors, so significance tests become unreliable. The standard fix is not to abandon OLS but to use heteroskedasticity-robust standard errors, which is now the default in most applied work.
Where this is taught
Definitions are the trailer. These free levels turn Heteroskedasticity into something you play — one bite-size lesson, with worked examples, a quiz and XP.