Date: Fri, 5 May 2006 14:58:14 -0700
Reply-To: David L Cassell <davidlcassell@MSN.COM>
Sender: "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From: David L Cassell <davidlcassell@MSN.COM>
Subject: Re: Speaking of training wheels
Content-Type: text/plain; format=flowed
>Now that I have completed my little project I would like to continue my
>study. My thought was to take the same data set and rewrite my program a
>times and experiment with different types of analysis and different
>approaches to the coding (hopefully to make it more logical and more
>efficient). Mainly I know i need practice but I don't want to pursue some
>irrelevent tangent. If you were to devise a "basic training" course for a
>complete newbie what would it include? How would it be the same or
>from the way you learned, etc?
>The type of work i expect to do will be in the vein of institutional
>research. Therefore there will be lots of issues regarding reconciling data
>from several different databases (different types) and comparing every
>metric in the world as a function of demographic variables (race, gender,
>etc.). In this kind of work i imagine the statistical demands are not high
>but being able to code efficiently will be a key I think.
>Any thoughts would be appreciated.
I think that one of the best training tools is SAS-L itself.
Take a SAS-L problem that interests you, and seems like it might be
relevant to what you'll be doing. Try to solve it.
Think about what you can do, and what you have to guess about,
and what the poster needs to explain. This is *exactly* like working
in oyur area, since you'll usually be given tasks which may or may *not*
be written clearly enough to complete. You can learn now how to
find the flaws i nthe task statements, and how to ask the right
questions after you read the statement.
Then code up a solution. You may have to fake some data in order
to test your code. SAS-L is a good way to learn how to do that, too.
There are plenty of responses where someone creates a test data set,
and that code is another learning tool. Test your code. Fix any bugs.
After that, look at the solutions other people have contributed. This
is the real reason SAS-L is a great learning tool, because anywhere else
you are either:  left with no idea of how good or bad your answer
is; or  left with a single solution which is hard to evaluate against
your own work. Sometimes, there will be a dozen different answers,
and you can learn all kinds of new approaches by studying those
answers, then comparing them to your own.
Once you start having better answers than some of the posters, it is
time to start posting your answers. As someone once said, "When you
can snatch the pebble from my hand..."
David L. Cassell
3115 NW Norwood Pl.
Corvallis OR 97330
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