residual plot

A residual plot IS a specific kind of scatter plot: it plots residuals (errors) against fitted values or predictors as a scatter of points. A competent speaker would call a residual plot 'a scatter plot' — the points encode fitted value on x-axis and residual on y-axis.

A residual plot needs residuals to operate now — it cannot exist or function without residuals (the differences between observed and predicted values). Remove residuals and the plot has no data to display. This is a present-tense dependency, not a historical one.

A residual plot IS a specific kind of diagnostic plot — it assesses regression model assumptions by plotting residuals against fitted values to reveal non-linearity, heteroscedasticity, or other model inadequacies. The note pins the sense correctly: a competent speaker would call a residual plot 'a diagnostic plot'. Direction is specific→general.

Residual plot serves residual analysis: it is designed to help analysts check model assumptions by visualizing residuals for patterns, heteroscedasticity, or outliers. The plot exists to further the operation of residual analysis.

A residual plot IS a specific kind of regression diagnostic. It displays residuals (observed minus fitted values) to diagnose model problems such as nonlinearity, heteroscedasticity, and outliers. A competent speaker would call it 'a regression diagnostic.' Direction: residual plot (specific) → regression diagnostic (general). Law 9.

A component-plus-residual plot IS a specific kind of residual plot used in regression diagnostics. It displays the relationship between a response variable and a predictor, adding the predictor's linear effect. Direction: specific→general. Law 9.