Proc univariate histogram rename x axis
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The comparative CDF plot shows the empirical distributions. * create comparative histograms and CDF plots */ * transpose from wide to long data format to create a CLASS variable */ proc transpose data=Wide name=ID out=Long ( drop=i ) by i run * simulate three variables with different distributions */ data Wide The following call to PROC UNIVARIATE creates these "comparative CDF plots," as well as the comparative histograms, for simulated data: This plot does not reveal anything about the distribution of the third variable.Ī different way to compare distributions is to plot a panel of the empirical cumulative distribution functions (CDF). Consequently, all data in the bottom panel is inside of a single histogram bin. The variable in the top histogram has a range that is 10 times the range of the variable in the lower histogram. To illustrate this, consider the following comparative histogram of three widely varying quantities: If one of the variables has a range that is an order of magnitude greater than the range of another variable, the comparative histogram can lose its effectiveness. However, for three or more distributions, an overlay of histograms can be difficult to read. This method works well for two distributions.
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Use transparency to overlay two histograms on the same axis. The comparative histogram is produced automatically by PROC UNIVARIATE when the analysis includes a classification variable. I have used this approach to compare salaries between two categories of workers. One technique is to display a panel of histograms, which are known as comparative histograms. The usual way to compare data distributions is to use histograms. More generally, you might be interested in visualizing how the distribution of one variable differs from the distribution of other variables. Questions you might ask include "Which variable has the largest spread?" and "Which variables exhibit skewness?" Suppose that you have several data distributions that you want to compare.