heteroscedasticity

listen to the pronunciation of heteroscedasticity
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The property of a series of random variables of not every variable having the same finite variance
(İstatistik) In statistics, a sequence or a vector of random variables is heteroscedastic if the random variables have different variances. The complementary concept is called homoscedasticity. (Note: The alternative spelling homo- or heteroskedasticity is equally correct and is also used frequently.) The term means "differing variance" and comes from the Greek "hetero" ('different') and "skedastios" ('dispersion')
A term which refers to situations in which the variability of the residuals is not constant Most statistical procedures such as regression and analysis of variance assume that the variability of the residuals is constant everywhere If heteroscedasticity is observed, it may often be removed by transforming the dependent variable using a square root or a logarithm
when the values of residuals tend to change systematically as the independent variable increases
"Mixed scatter " A scatterplot or residual plot shows heteroscedasticity if the scatter in vertical slices through the plot depends on where you take the slice Linear regression is not usually a good idea if the data are heteroscedastic
In regression analysis the condition of nonconstant variance
Time-varying, or time-dependent, variance
Data are heteroscedastic when the variances within groups of observations are unequal Data in a regression are heteroscedastic when the variance of the dependent variable depends on the level of the independent variable Data in a t-test or analysis of variance are heteroscedastic when the variances of the observations within each group are unequal across groups