The script adds the result of the Grubb's test to a Distribution platform and opens the normal quantile plot to so that you can assess normality of the sample, inferring that the population is normally distributed. If the data are otherwise normally distributed but contain a discordant outlier, it might fail a normality test but you should still see linearity in the plot. Regardless of the outlier, non-normal data should not appear linear in this plot. The normal quantile plot should make it clear if this is the case.

If this example is univariate, then where do 'residuals' come from?

Learn it once, use it forever!