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Added variable plot of linear regression model

`plotAdded(mdl)`

`plotAdded(mdl,coef)`

`plotAdded(mdl,coef,Name,Value)`

`h = plotAdded(___)`

`plotAdded(`

produces an added variable plot for the whole model `mdl`

)`mdl`

except
the constant (intercept) term.

`plotAdded(`

specifies graphical properties of adjusted data points using one or more name-value
pair arguments. For example, you can specify the marker symbol and size for the data
points.`mdl`

,`coef`

,`Name,Value`

)

returns
line objects using any of the input argument combinations in the previous syntaxes.
Use `h`

= plotAdded(___)`h`

to modify the properties of a specific line after you
create the plot. For a list of properties, see Line Properties.

The data cursor displays the values of the selected plot point in a data tip (small text box located next to the data point). The data tip includes the

*x*-axis and*y*-axis values for the selected point, along with the observation name or number.

A

`LinearModel`

object provides multiple plotting functions.When creating a model, use

`plotAdded`

to understand the effect of adding or removing a predictor variable.When verifying a model, use

`plotDiagnostics`

to find questionable data and to understand the effect of each observation. Also, use`plotResiduals`

to analyze the residuals of the model.After fitting a model, use

`plotAdjustedResponse`

,`plotPartialDependence`

, and`plotEffects`

to understand the effect of a particular predictor. Use`plotInteraction`

to understand the interaction effect between two predictors. Also, use`plotSlice`

to plot slices through the prediction surface.

`plotAdded`

shows the incremental effect on the response of specified terms by removing the effects of the other terms, whereas`plotAdjustedResponse`

shows the effect of a selected predictor in the model fit with the other predictors averaged out by averaging the fitted values. Note that the definitions of adjusted values in`plotAdded`

and`plotAdjustedResponse`

are not the same.