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.
Statistical software provides methods to simulate independent random variates from continuous and discrete distributions. For example, in the SAS DATA step, you can use the RAND function to simulate variates from continuous distributions (such as the normal or lognormal distributions) or from discrete distributions (such as the Bernoulli or Poisson).
In a previous article, I presented some of the most popular blog posts from 2023. The popular articles tend to discuss elementary topics that have broad appeal. However, I also wrote many technical articles about advanced topics. The following articles didn't make the Top 10 list, but they deserve a
An unobserved category is one that does not appear in a sample of data. For example, in a small sample of US voters, you are likely to observe members of the major political parties, but less likely to observe members of minor or fringe parties. This can cause a headache
In 2023, I wrote 90 articles for The DO Loop blog. My most popular articles were about SAS programming, data visualization, and statistics. In addition, several "general interest" articles were popular, including my article for Pi Day and an article about AI chatbots. If you missed any of these articles,
Statistical software often includes supports for a weight variable. Many SAS procedures make a distinction between integer frequencies and more general "importance weights." Frequencies are supported by using the FREQ statement in SAS procedures; general weights are supported by using the WEIGHT statement. An exception is PROC FREQ, which contains
SAS provides many built-in routines for data analysis. A previous article discusses polychoric correlation, which is a measure of association between two ordinal variables. In SAS, you can use PROC FREQ or PROC CORR to estimate the polychoric correlation, its standard error, and confidence intervals. Although SAS provides a built-in
Correlation is a statistic that measures the association between two variables. When two variables are positively correlated, low values of one variable tend to be associated with low values of the other variable. Medium values and high values are similarly associated. For negative correlation, the association is flipped: low values
These are a few of my favorite things. —Maria in The Sound of Music For my annual Christmas-themed post, I decided to forgo fractal Christmas trees and animated greeting cards and instead present a compilation of some of my favorite data visualization tips for advanced SAS users. Hopefully, this
A previous article discussed how to compute probabilities for the bivariate standard normal distribution. The standard bivariate normal distribution with correlation ρ is denoted BVN(0,ρ). For any point (x,y), you can use the PROBBNRM function in SAS to compute the probability that the random variables (X,Y) ~ BVN(0,ρ) is observed
This article shows how to use SAS to compute the probabilities for two correlated normal variables. Specifically, this article shows how to compute the probabilities for rectangular regions in the plane. A second article discusses the computation over infinite regions such as quadrants. If (X,Y) are random variables that are
