Residual plots play an important role in regression analysis when the goal is to confirm or negate the individual regression assumptions, identify outliers, and/or assess the adequacy of the fitted model. Residual plots are graphical representations of the residuals, usually in the form of two-dimensional graphs. In other words, residual plots attempt to show relationships between the residuals and either the explanatory variables (X1, X2, …, Xp), the fitted values (Ŷi) index numbers (1, 2, …, n), or the normal scores (values from a random sample from the standard normal distribution), among others, often using scatterplots. Before this entry discusses the types of individual residual plots in greater detail, it reviews the concept of residuals in regression analysis, including different types of residuals, emphasizing the ...

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