The variance of the error variable
is required to be constant.When this requirement is violated, the condition is called heteroscedasticity.
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Q10: When the variance Q14: The least squares method requires that the Q86: Data that exhibit an autocorrelation effect violate Q243: We standardize residuals by subtracting their mean Q246: If the plot of the residuals vs.the Q250: An outlier is an observation that is Q255: We check for normality by drawing a Q257: The plot of residuals vs.predicted values should Q264: If the plot of the residuals is Q272: If the variance of the errors is![]()
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