Theoretical Statistics
Homoscedasticity refers to the property of a dataset where the variance of the dependent variable is constant across all levels of an independent variable. This concept is crucial in regression analysis because it ensures that the errors or residuals are uniformly distributed, which is an essential assumption for many statistical methods. When homoscedasticity holds, it implies that predictions made by a model are reliable, as the spread of residuals remains consistent across different values of the predictor variable.
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