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.
A previous article shows how to interpret the collinearity diagnostics that are produced by PROC REG in SAS. The process involves scanning down numbers in a table in order to find extreme values. This can be a tedious and error-prone process. Friendly and Kwan (2009) compare this task to a
The Johnson system (Johnson, 1949) contains a family of four distributions: the normal distribution, the lognormal distribution, the SB distribution, and the SU distribution. Previous articles explain why the Johnson system is useful and show how to use PROC UNIVARIATE in SAS to estimate parameters for the Johnson SB distribution
You can represent every number as a nearby integer plus a decimal. For example, 1.3 = 1 + 0.3. The integer is called the integer part of x, whereas the decimal is called the fractional part of x (or sometimes the decimal part of x). This representation is not unique.
A SAS programmer wanted to create a graph that illustrates how Deming regression differs from ordinary least squares regression. The main idea is shown in the panel of graphs below. The first graph shows the geometry of least squares regression when we regress Y onto X. ("Regress Y onto X"
Recently someone on social media asked, "how can I compute the required sample size for a binomial test?" I assume from the question that the researcher was designing an experiment to test the proportions between two groups, such as a control group and a treatment/intervention group. They wanted to know
In a previous article, I showed how to perform collinearity diagnostics in SAS by using the COLLIN option in the MODEL statement in PROC REG. For models that contain an intercept term, I noted that there has been considerable debate about whether the data vectors should be mean-centered prior to
The Johnson system (Johnson, 1949) contains a family of four distributions: the normal distribution, the lognormal distribution, the SB distribution (which models bounded distributions), and the SU distribution (which models unbounded distributions). Note that 'B' stands for 'bounded' and 'U' stands for 'unbounded.' A previous article explains the purpose of
I was recently asked about how to interpret the output from the COLLIN (or COLLINOINT) option on the MODEL statement in PROC REG in SAS. The example in the documentation for PROC REG is correct but is somewhat terse regarding how to use the output to diagnose collinearity and how
From the early days of probability and statistics, researchers have tried to organize and categorize parametric probability distributions. For example, Pearson (1895, 1901, and 1916) developed a system of seven distributions, which was later called the Pearson system. The main idea behind a "system" of distributions is that for each
In my book Simulating Data with SAS, I show how to use a graphical tool, called the moment-ratio diagram, to characterize and compare continuous probability distributions based on their skewness and kurtosis (Wicklin, 2013, Chapter 16). The idea behind the moment-ratio diagram is that skewness and kurtosis are essential for
