Rick Wicklin, PhD, is a distinguished researcher in computational statistics at SAS and is a principal developer of SAS/IML software. His areas of expertise include computational statistics, simulation, statistical graphics, and modern methods in statistical data analysis. Rick is author of the books Statistical Programming with SAS/IML Software and Simulating Data with SAS.
In statistics, the normal (Gaussian) distribution serves as a reference for many statistical quantities. For example, a normal distribution has excess kurtosis equal to zero, and other distributions are classified as leptokurtic (heavier-than-normal tails) or platykurtic (lighter-than-normal tails) in comparison. Similarly, the standard deviation of a normal distribution (σ) is
A previous article shows how to use PROC FCMP to define the PDF, CDF, and quantile functions for the three-parameter Burr XII distribution. I also defined the log-PDF function, which is used during maximum likelihood estimation (MLE) of parameters. This article shows how to fit the Burr distribution to data
SAS supports more than 25 common probability distributions for the PDF, CDF, QUANTILE, and RAND functions. If you need a less-common distribution, you can implement new distributions by using Base SAS (specifically, PROC FCMP) or the SAS/IML language. This article shows how to use call functions related to the three-parameter
There are many ways to visualize the distribution of univariate data. A previous article presents an overview and shows how to use SAS to create histograms, kernel density estimates, box plots, and cumulative distribution plots. This article continues the visualization journey, with an emphasis on dot plots and heat maps.
In a previous article, I presented some of the most popular blog posts from The DO Loop in 2025. In general, popular articles deal with elementary topics that have broad appeal. However, I also write technical articles about advanced topics, which typically do not make it onto a Top 10
There are many ways to visualize the distribution of univariate data: histograms, kernel density estimates, box plots, and more. Visualizing a distribution leads to better insights than merely displaying statistics such as the sample mean, standard deviation, and quantiles. In fact, there are many well-known examples of data sets that
In 2025, I wrote about 60 articles for The DO Loop blog. My most popular articles were about SAS programming, data visualization, and statistics. This blog post lists some of the most popular articles from 2025. Read on for the Reader's Choice Awards in various categories! SAS Programming The following
Rockin' around the Christmas tree, Have a happy holiday – Brenda Lee An internet search for "How many lights do I need for my Christmas tree," returns many opinions. A popular answer is that you need "one strand of lights for each foot of your tree." Another common answer is
In univariate data analysis, the median is often used as an alternative to the mean because the mean is sensitive to outliers in the data, whereas the median is a robust statistic. For higher-dimensional data, the mean and the centroid are both used to represent the "center" of a cloud
Recently, a colleague struggled to find the source of a run-time error happening somewhere within a very large library of SAS IML function modules. Since the error happens at run time, I told my colleague about how to find the location of a run time error by reading the traceback
