Normality Tests

The qqnorm plot produces  a quantile-quantile plot which has the data being tested on one axis and the corresponding quantiles of a standard normal distribution on the other. 

The density plot is a  smooth version of the histogram; i.e., smooth estimates of the population frequency or probability density.  Using “width=2iqd” in density, sets the degrees of smoothness of the density plot a good way.

Histogram and density ⇒ best picture of the population shape

The qqnorm and boxplot ⇒ best picture of outliers

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Transcript

Now, a very useful test is the test for normality. And the easy way to see that is a so-called quantile-quantile log, otherwise known as a qqnorm plot.  And what this is going to show is we're going to have the data being tested on one axis, and the corresponding quartiles of the normal distribution plotted on the other [axis]. And we're going to look and see this does this fall along a line.  Now a density plot is basically a smoothed version of the histogram.  And we can also plot the histogram and the density plot to show the population shape.  And we will plug the qqnorm and a boxplot, and that's going to make it very easy is for us to see the outliers. So what does this do?