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Overconfidence is a good thing for decision makers.
Heteroscedasticity
A condition in regression analysis where the variance of the error terms is not constant across all levels of the independent variables, violating uniform variance assumptions of ordinary least squares regression.
Homoscedasticity
A condition in regression analysis where the variance of error terms (residuals) is constant across all levels of an independent variable.
Variance
A metric that quantifies the variability or distribution range of a data set, determined by the mean of the squared deviations from the mean value.
Residuals
Differences between observed values and the values predicted by a statistical model, indicating the error in predictions.
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