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  • https://stats.libretexts.org/Bookshelves/Computing_and_Modeling/Supplemental_Modules_(Computing_and_Modeling)/Regression_Analysis/Simple_linear_regression/Diagnostics_for_residuals(continued)
    In this plot, the ordered residual (or observed quantiles) of the residuals are plotted aginst the expected quantiles assuming that \(\epsilon_i\)'s are approximately normal and independent with mean ...In this plot, the ordered residual (or observed quantiles) of the residuals are plotted aginst the expected quantiles assuming that \(\epsilon_i\)'s are approximately normal and independent with mean 0 and variance = MSE. Heteroscedasticity or unequal variance: the variance of the error \(\epsilon\)i may sometimes depend on the value of Xi. This is often true for financial data, where the volume of transactions usually has a role in the uncertainty of the market.

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