Lionel Loosefit is on trial for violating the assumptions of regression analysis. During day one the prosecution presented evidence showing that the errors in Loosefit’s model were not normally distributed. During day two, the evidence was put to the test during reexamination. Today, the prosecution addresses the second alleged violation: The errors in the defendant’s regression model are not independent. Minnie Tabber, a world-renowned statistician, is on the witness stand.

Prosecutor: Let me remind the members of the jury that a residual is simply the difference between the data value estimated by the regression model and the actual observed data value. Now, the law clearly states that besides being normally distributed, residuals should be independent. Why is that so important, Dr. Tabber?

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