More generally, to create a linear regression model, use the `fitlm()`

function. This function creates a `LinearModel`

object. The object in the workspace has a series of properties that can be immediately viewed by simply clicking on it. Methods such as `plot`

, `plotResiduals`

, and `plotDiagnostics`

are available if you want to create plots and perform a diagnostic analysis.

### Note

`LinearModel`

is an object comprising training data, model description, diagnostic information, and fitted coefficients for a linear regression.

By default, `fitlm()`

takes the last variable in the table or dataset array as the response. Otherwise, we have to specify predictors and response variables, for example, as a formula. In addition, we can set a specific column as the response variable by using the `ResponseVar`

name-value pair argument. To use a set of the columns as predictors, use the `PredictorVars`

name-value pair argument. Predictor variables can be numeric or of any grouping variable...