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Are Blacks and Hispanics too Lazy to be Statisticians?

I am at the Western Users of SAS Software conference this week and just like the Joint Statistical Meetings, SAS Global Forum and SPSS Directions, there is about as much diversity here as at the Republican National Convention. I brought this up here and at two other meetings I attended. Each time at least some…

Why the cool kids won’t hang out with you: A guide to mentors

Many years ago, when I was a young MBA student, we were all advised to find mentors who would help our careers.  However, I found that many people I was interested in were not particularly interested in me. That was disappointing and irritating.  After all, I believed I was a smart, hard-working person and I…

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New Semester, New SAS On-Demand for Academics

If you had SAS On-Demand for Academics installed last year and you want to continue using it in the new academic year, you need to uninstall your previous version and install the new version. You can find more details here  – http://support.sas.com/ondemand/SAS93.html Okay, so I uninstalled the previous version of Enterprise Guide no problem. The SAS…

The Type of Appreciation Blog Readers Ought to Be Showing

Yesterday, I posted how to get SPSS Integration Technologies with Python working on the Mac. Today, I received this certificate of appreciation from one of my blog readers.   I’m including this in my performance review. Oh wait, I don’t get performance reviews, I’m the president. Now that I have my certificate in getting the…

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Interview with a Vampire Researcher: What I was doing at JSM

I hate Buffy the Vampire Slayer and the entire Twilight Series. This came about over the course of a week when my daughter had strep throat and was watching approximately 4,789,362 episodes of vampire shows in the living room, which is just down the hall from my office. Thus, when Brenda Osuna from USC asked…

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Choosing the Right Propensity Score Method: A statistics fable

Once upon a time there were statisticians who thought the answer to everything was to be as precise, correct and “bleeding edge” as possible. If their analyses were precise to 12 decimal places instead of 5, of course they were better because as everyone knows , 12 is more than 5 (and statisticians knew it…