When homoscedasticity occurs variance of the error term The regression model is constant. …in contrast, heteroscedasticity occurs when the variance of the error term is not constant.

What does heteroscedasticity mean?

As it relates to statistics, heteroscedasticity (also known as heteroskedasticity) refers to Error variance or scattering dependence within at least one independent variable in a particular sample. . . This provides guidelines about the probability that a random variable differs from the mean.

What is an example of heteroscedasticity?

example. Heteroskedasticity usually occurs when observations are very different in size.A typical example of heteroscedasticity is Income versus meal expenditure. As a person’s income increases, so does the variability in food consumption.

What does homoscedasticity in statistics mean?

In regression analysis, homoscedasticity means The case where the variance of the dependent variable is the same for all data. Homoscedasticity helps the analysis because most methods are based on the assumption of equal variances.

What does heteroskedasticity in regression mean?

heteroscedasticity means When residual variances are unequal across a series of measurements. When running a regression analysis, heteroscedasticity results in uneven dispersion of residuals (also known as error terms).

Heteroskedasticity Summary

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