The DO Loop
Statistical programming in SAS with an emphasis on SAS/IML programs
My last post was a criticism of a statistical graph that appeared in Bloomberg Businessweek. Criticism is easy. Analysis is harder. In this post I re-analyze the data to present two graphics that I think should have replaced the one graphic in Businessweek. You can download the SAS program that
Recently I read a blog that advertised a data visualization competition. Under the heading "What Are We Looking For?" is a link to a 2007 Bloomberg Businessweek graph that visualizes how participation in online social media activities vary across age groups. The graph is reproduced below at a smaller scale:
Errors. We all make them. After all, “to err is human.” Or, as programmers often say, “To err is human, but to really foul things up requires a computer” (Farmer’s Almanac, 1978). This post describes how to interpret error messages from PROC IML that appear in the SAS log. The
I am thankful to be a statistical programmer. When I wake up in the morning, I am eager to start my day. I love statistics, programming, and working at SAS, and I write my blog to share that joy. This a Golden Age for statistical programmers because theoretical ideas and
I give many presentations and workshops on how to use SAS/IML Studio, and more than once I have been asked about how to launch the program. Sometimes the inquiry hints at mild frustration, such as last week's "How do I RUN the $%#@# THING!!!!" The email I got this week
In a previous post, I used statistical data analysis to estimate the probability that my grocery bill is a whole-dollar amount such as $86.00 or $103.00. I used three weeks' grocery receipts to show that the last two digits of prices on items that I buy are not uniformly distributed.