MTH-416, REGRESSION ANALYSIS Lecture Notes - Lecture 10: Indian Institute Of Technology Kanpur, Heteroscedasticity, 2 On

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In the multiple regression model y x it is assumed that. This property of constancy of variance is termed as homoskedasticity and disturbances are called as homoskedastic disturbances. In many situations, this assumption may not be plausible, and the variances may not remain the same. The disturbances whose variances are not constant across the observations are called heteroskedastic disturbance, and this property is termed as heteroskedasticity. In this case and disturbances are pairwise uncorrelated. Graphically, the following pictures depict homoskedasticity and heteroskedasticity. Examples: suppose in a simple linear regression model, x denote the income and y denotes the expenditure on food. It is observed that as the income increases, the expenditure on food increases because of the choice and varieties in food increase, in general, up to a certain extent. So the variance of observations on y will not remain constant as income changes.

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