SAS Learning Post
Technical tips and tricks from SAS instructors, authors and other SAS experts.![Random Sampling: What's Efficient?](https://blogs.sas.com/content/sastraining/files/2015/09/random_sampling.jpg)
Suppose you wish to select a random sample from a large SAS dataset. No problem. The PROC SURVEYSELECT step below randomly selects a 2 percent sample: proc surveyselect data=large out=sample method=srs /* simple random sample */ n=1000000; /* sample size */ run; Do you have a SAS/STAT license? If not,
![What’s wrong with this SAS program?](https://blogs.sas.com/content/sastraining/files/2017/01/ProgrammingTips-1.png)
I think everyone can agree that being able to debug programs is an important skill for SAS programmers. That’s why Susan Slaughter and I devoted a whole chapter to it in The Little SAS® Book. I don’t know about you, but I think figuring out what’s wrong with my program
![Analytics 2015 lands in Rome on Nov. 9-11](https://blogs.sas.com/content/sastraining/files/2015/09/Analytics2015_Rome.jpg)
The digital disruption phenomenon is redrawing the market map. New players, products and services are gaining competitive advantage, while traditional business and revenue models are being questioned. Gartner believes that by 2020, thanks to the Internet of Things, information will be used to reinvent, digitalize or eliminate 80% of business
![Serving up SAS training in cities near you](https://blogs.sas.com/content/sastraining/files/2015/09/racketwithballs.jpg)
The 2015 United States Tennis Open tournament is now underway, and like most tennis fans, I’ve got my eyes on women’s tennis great Serena Williams, as she attempts to make history by winning the tournament and achieving a calendar Grand Slam. What are her chances of reaching the milestone? Most
![Reading Hierarchical Data - Part 3](https://blogs.sas.com/content/sastraining/files/2017/01/LearnSAS-1.png)
This post is the third and final in a series that illustrates three different solutions to "flattening" hierarchical data. Don't forget to catch up with Part 1 and Part 2. Solution 2, from my previous post, created one observation per header record, with detail data in a wide format, like
![The one piece of advice everyone in analytics needs to hear](https://blogs.sas.com/content/sastraining/files/2015/08/conversation.jpg)
I was recently asked why I would recommend my new class, Explaining Analytics to Decision Makers: Insights to Action. The answer goes back to some great advice, a lunch of eggplant parmesan and in another more twisted way, to what was ironically affectionately known as the “bomb plant.” Early in