def METHOD_NAME(
    model: statsmodels.regression.linear_model.RegressionResultsWrapper,
    dependent_variable: pd.Series,
    plot: bool = True,
    export: str = "",
    sheet_name: Optional[str] = None,
    external_axes: bool = False,
):
    """Show Durbin-Watson autocorrelation tests
    Parameters
    ----------
    model : OLS Model
        A fit statsmodels OLS model.
    dependent_variable : pd.Series
        The dependent variable for plotting
    plot : bool
        Whether to plot the residuals
    export : str
        Format to export data
    external_axes : bool, optional
        Whether to return the figure object or not, by default False
    """
    fig = OpenBBFigure(
        yaxis_title="Residual", xaxis_title=dependent_variable.name.capitalize()
    )
    autocorr = regression_model.get_dwat(model)
    if 1.5 < autocorr < 2.5:
        console.print(
            f"The result {autocorr} is within the range 1.5 and 2.5 which therefore indicates "
            f"autocorrelation not to be problematic."
        )
    else:
        console.print(
            f"The result {autocorr} is outside the range 1.5 and 2.5 and could "
            f"be problematic. Please consider lags of the dependent or independent variable."
        )
    if not fig.is_image_export(export):
        export_data(
            export,
            os.path.dirname(os.path.abspath(__file__)),
            f"{dependent_variable.name}_dwat",
            autocorr,
            sheet_name,
        )
    if plot or fig.is_image_export(export):
        fig.set_title("Plot of Residuals")
        fig.add_scatter(
            x=dependent_variable,
            y=model.resid,
            mode="markers",
        )
        fig.add_hline(y=0, line=dict(color="red", dash="dash"))
        if fig.is_image_export(export):
            export_data(
                export,
                os.path.dirname(os.path.abspath(__file__)),
                f"{dependent_variable.name}_residuals",
                dependent_variable,
                sheet_name,
                fig,
            )
        return fig.show(external=external_axes)
    return None