Thanksgiving turkey, Blue Jays playoff baseball, and SAS ANALYTICS all in one day!
Thanksgiving is a wonderful holiday. The air is crisp, fall colours are at their peak, family and friends abound, and a veritable feast is at hand. This year was especially good because Thanksgiving Day included three of my favourite things: roast turkey, Blue Jays playoff baseball and coding in SAS/STAT.
First the baseball. If you are a SAS User residing in the U.S. then you are thinking that baseball is over by Thanksgiving, right? That’s true, unless you live in Canada. The Toronto Blue Jays defeated the Texas Rangers on October 9 (Thanksgiving in Canada) to win the American League Division Series. Let’s not discuss the AL Championship Series.
The roast turkey, as a Thanksgiving tradition, needs no explanation. The real story here is how SAS/STAT found its way on to my Thanksgiving Day menu.
It is natural to enjoy perks from family members’ occupations: retail employee pricing, airline benefits, medical advice, etc. Are there any perks from having a statistician in the family? Yes indeed. And one who knows SAS programming, even better.
My niece, Meaghan, sent me a note before the Canadian Thanksgiving weekend to let me know that she was bringing home research data from the University of Ottawa, where she is a Masters candidate in the Department of Biology. We were gathering at her parents’ home in Annan Ontario, overlooking the Georgian Bay of Lake Huron (exquisite view!). She had some questions regarding the statistical analyses. When we sat down to review the study and the data, I noticed that she was using two software packages: MS Excel (okay, I guess), and another package that will remain nameless. I joked that I could not help her until the offending file was deleted from my view. Meaghan explained that she would like to use SAS, but that it is too expensive. Ah ha! “Not so, mon ami.”
It did not take long to explain that SAS University Edition is free for use to students and faculty and suggested she download it. Within a few hours, Meaghan had SAS installed on her MacBook (!). In no time she was able to execute the SAS program that I helped her code to import her data from a CSV file, transform it for a mixed model analysis, and run several candidate models using the GLIMMIX Procedure. Meaghan’s study is a classic split-split-plot design where the plots, in this case, are rabbits. Seven replicates were measured in the smallest unit, and different rabbits were “measured” at 3 times: 4, 8, and 12 weeks. But it is better if I turn this blog over to Meaghan to explain the study and how she is learning SAS.