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Mike Gilliland 0
More research from Harvard Business Review

There is something that 90% of us admit to doing, and the other 10% will lie about. That, of course, is Googling yourself. As an avid follower of myself, and everything I do, I look forward to a weekly Google Alert that tells me all about what I've been up to.

Chris Hemedinger 0
Making up for lost time (UTC vs. DST)

Did you oversleep this morning? If you live in the United States of America, Monday morning seems to have arrived just a bit earlier, accompanied by a bit more "dark" than usual. That's because as good time-fearing citizens, we have all set our clocks ahead by one hour so as

Rick Wicklin 0
Compute sample quantiles by using the QNTL call

SAS provides several ways to compute sample quantiles of data. The UNIVARIATE procedure can compute quantiles (also called percentiles), but you can also compute them in the SAS/IML language. Prior to SAS/IML 9.22 (released in 2010) statistical programmers could call a SAS/IML module that computes sample quantiles. With the release

Rick Wicklin 0
Quantiles of discrete distributions

I work with continuous distributions more often than with discrete distributions. Consequently, I am used to thinking of the quantile function as being an inverse cumulative distribution function (CDF). (These functions are described in my article, "Four essential functions for statistical programmers.") For discrete distributions, they are not. To quote

Chris Hemedinger 0
Be a code poet laureate

The next time you write a DATA step, try to express it in iambic pentameter.  Or instead of a SAS macro function, how about a SAS macro sonnet?  (Or, for the more base among you, a limerick?) That's the spirit behind the code {poems} project.  You write a poem in

Rick Wicklin 0
Testing data for multivariate normality

I've blogged several times about multivariate normality, including how to generate random values from a multivariate normal distribution. But given a set of multivariate data, how can you determine if it is likely to have come from a multivariate normal distribution? The answer, of course, is to run a goodness-of-fit

Learn SAS
Shelly Goodin 0
SAS author's tip: Alternative ODS destinations

Neil Constable is a Principal Education Consultant at SAS in the United Kingdom, where he applies his extensive knowledge of Base SAS, SAS Enterprise Guide, and the SAS business intelligence tools. He's also the author of SAS Programming for Enterprise Guide Users, Second Edition--and this week's featured tip. You can get to know Neil

Mike Gilliland 0
APICS e-News: Demand planning analysts are hot

Citing online job postings reviewed by talent data firm Wanted Analytics, and a Software Advice  blog by Michael Koploy, APICS e-News reports that "Demand planning analysts" are hot -- one of the five hottest careers in logistics.  (Free subscription to APICS e-News) Clearly, APICS means there are a lot of good jobs

Mike Gilliland 0
New blog header design by Mr. Blackwell

Recently I complained about the stock art used on The BFD blog header. So I was foaming with excitement when Alison Bolen (who oversees the SAS blogging platform) kindly took notice, and enlisted Mr. Blackwell to come up with something more pleasing and appropriate.     OMG Mr. Blackwell!!! As a huge fan of

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