# The DO Loop

Statistical programming in SAS with an emphasis on SAS/IML programsPlot rates, not counts. This maxim is often stated by data visualization experts, but often ignored by practitioners. You might also hear the related phrases "plot proportions" or "plot percentages," which mean the same thing but expresses the idea alliteratively. An example in a previous article about avoiding alphabetical ordering

Converting a program from one language to another can be a challenge. Even if the languages share many features, there is often syntax that is valid in one language that is not valid in another. Recently, a SAS programmer was converting a program from R to SAS IML. He reached

Howard Wainer, who used to write the "Visual Revelations" column in Chance magazine, often reminded his readers that "we are almost never interested in seeing Alabama first" (2005, Graphic Discovery, p. 72). His comment is a reminder that when we plot data for a large number of categories (states, countries,

Sometimes it is helpful to display a table of statistics directly on a graph. A simple example is displaying the number of observations and the mean or median on a histogram. In SAS, the term inset is used to describe a table that is displayed on a graph. This article

In several previous articles, I've shown how to use SAS to fit models to data by using maximum likelihood estimation (MLE). However, I have not previously shown how to obtain standard errors for the estimates. This article combines two previous articles to show how to obtain MLE estimates and the

A previous article shows how to use Monte Carlo simulation to approximate the sampling distribution of the sample mean and sample median. When x ~ N(0,1) are normal data, the sample mean is also normal, and there are simple formulas for the expected value and the standard error of the