What is the difference between Homoscedasticity and Heteroscedasticity

If you recall that homogeneous means uniform or identical, whereas heterogeneous is defined as assorted or different, you may have an easier time remembering the concept of heteroskedasticity forever.Heteroskedasticity, in statistics, is when the standard deviations of a variable, monitored over a specific amount of time, are nonconstant.Is that homoscedasticity is (statistics) a property of a set of random variables where each variable has the same finite variance while heteroscedasticity is (statistics) the property of a series of random variables of not every variable having the same finite variance.Specifically, heteroscedasticity is a systematic change in the spread of the residuals over the range of measured values.Homoscedasticity and heteroscedasticity refer, respectively, to whether the variances of the predictions determined by regression remain constant or differ.

Annual income might be a heteroscedastic variable when predicted by age, because most teens aren't flying around in g6 jets that they bought from their own income.The underlying concepts are really very simple) you must do this in an easy to understand manner using the terminology of statistics or econometrics.The inverse of heteroscedasticity is homoscedasticity, which indicates that a dv's variability is equal across values of an iv.Treatment of patient results in success i.e.(don 't let the words intimidate you:

A simple bivariate example can help to illustrate heteroscedasticity:Heteroscedasticity is an antonym of homoscedasticity.As its roots imply it is a matter of (approximately) equal scatter, with nothing else implied.$\begingroup$ homoscedasticity term is used to represent dispersion in continuous data.