Do you want to bin a numeric variable into a small number of discrete groups? This article compiles a dozen resources and examples related to binning a continuous variable. The examples show both equal-width binning and quantile binning. In addition to standard one-dimensional techniques, this article also discusses various techniques

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Binning transforms a continuous numerical variable into a discrete variable with a small number of values. When you bin univariate data, you define cut point that define discrete groups. I've previously shown how to use PROC FORMAT in SAS to bin numerical variables and give each group a meaningful name

Sometimes a little thing can make a big difference. I am enjoying a new enhancement of SAS/IML 15.1, which enables you to use a numeric vector as the column header or row header when you print a SAS/IML matrix. Prior to SAS/IML 15.1, you had to use the CHAR or

When my colleague, Robert Allison, blogged about visualizing the Mandelbrot set, I was reminded of a story from the 1980s, which was the height of the fractal craze. A research group in computational mathematics had been awarded a multimillion-dollar grant to purchase a supercomputer. When the supercomputer arrived and got

SAS supports more than 25 common probability distributions for the PDF, CDF, QUANTILE, and RAND functions. Of course, there are infinitely many distributions, so not every possible distribution is supported. If you need a less-common distribution, I've shown how to extend the functionality of Base SAS (by using PROC FCMP)

Is 4 an extreme value for the standard normal distribution? In high school, students learn the famous 68-95-99.7 rule, which is a way to remember that 99.7 percent of random observation from a normal distribution are within three standard deviations from the mean. For the standard normal distribution, the probability

In the SAS/IML language, a matrix contains data of one type: numeric or character. If you want to create a SAS data set that contains mixed-type data (numeric and character), SAS/IML 15.1 provides support to write multiple matrices to a data set by using a single statement. Specifically, the CREATE

Heat maps have many uses. You can use a heat map to visualize correlation matrices, to visualize longitudinal data ("lasagna plots"), and to visualize counts in any two-dimensional table. As of SAS 9.4m3, you can create heat maps in SAS by using the HEATMAP and HEATMAPPARM statements in PROC SGPLOT.

I recently showed how to create an annotation data set that will overlay cell counts or percentages on a mosaic plot. A mosaic plot is a visual representation of a cross-tabulation of observed frequencies for two categorical variables. The mosaic plot with cell counts is shown to the right. The

The mosaic plot is a graphical visualization of a frequency table. In previous articles, I showed how to create a mosaic plot in SAS by using PROC FREQ and how to define a template in the Graph Template Language (GTL) by using the MOSAICPARM statement. This article shows how to