Statistics MCQs, Data Analysis, Stat Software
Different available tests of heteroscedasticity and detection of Heteroscedasticity using Graphical techniques will be presented in this category.
The post is about the White test of heteroscedasticity. One important assumption of Regression is that the variance of the Error Term is constant across observations. If the error has a constant variance, then the errors are called homoscedastic, otherwise heteroscedastic. In the case of heteroscedastic errors (non-constant variance), the …
The Breusch Pagan test (named after Trevor Breusch and Adrian Pagan) is used to check for the presence of heteroscedasticity in a linear regression model. Assume our regression model is $Y_i = \beta_1 + \beta_2 X_{2i} + \mu_i$ i.e we have simple linear regression model, and $E(u_i^2)=\sigma_i^2$, where $\sigma_i^2=f(\alpha_1 + …
To perform the Breusch-Pagan test for the detection of heteroscedasticity, use the data from the following file Table_11.3. Step 1: The estimated regression is $\hat{Y}_i = 9.2903 + 0.6378X_i$ Step 2: The residuals obtained from this regression are: $\hat{u}_i$ $\hat{u}_i^2$ $p_i$ -5.31307 28.22873 0.358665 -8.06876 65.10494 0.827201 6.49801 42.22407 0.536485 …
One important assumption of Regression is that the variance of the Error Term is constant across observations. If the error has a constant variance, then the errors are called homoscedastic, otherwise heteroscedastic. In the case of heteroscedastic errors (non-constant variance), the standard estimation methods become inefficient. Typically, to assess the …