Tag Archives: Statistics

What’s in a name?

So why the name “The Log Cabin”?  Well, the reason is two-fold.  (1) I am constantly reminded about the general public’s lack-of-knowledge of and paranoia surrounding logs, or more specifically, logarithms.  For example, I’ve had the following exchange on more than one occasion:

Random acquaintence: “What do you study, Ryan?”

Me: “Mathematics and Statistics.”

RA:  “Wow; you must know a lot about logarithms.”

Ryan:  “Um, I guess I know a bit about them.  Probably nothing more than some other ‘special’ functions, e.g. sine, exponential, etc.”

RA: (shrieks and/or laughs nervously) “Yeah, did you see the score of the game?”

My best guess is that a person in RA’s shoes remembers “logarithm” because they think it’s a funny word or something.  I have no idea.  Any other hypotheses?

To hammer home the point, I recently read a NY Times article about using statistics to answer questions related to injury likelihood in professional baseball.  The author mentioned that the analysts “build logarithm formulas and computer codes that test Conte’s hypotheses…”  No shit!  The article is referenced at the bottom of this post.  As I said when I posted this on Facebook, I would bet that they did build a logit model (seems like a natural starting point), but this sounds like a gratuitous use of the word “logarithmic” in order to make them sound like mathematical geniuses or just plain nerds.

Um, Ryan, you said that there were two reasons.  Right.  Anyway, I needed something clever that can easily be coupled with log — naturally, a cabin.  And the cabin evokes memories of a youngster walking to a little red school house (a cabin) with their books tethered together with a leather strap slung over their shoulder.  OK, that may only work for the readers over 100 in age.

Nevertheless, this blog is going to be all about statistics and data in general.  I’ll touch on topics ranging from beginning statistics to my favorite problems and solutions from graduate school.  I hope to present solutions to classic problems as well as data mining topics (summarization, visualization, etc.) from the contemporary analytics world of Web 2.0.  The point here is that I am going to attempt to demystify statistics, hopefully educate some, and remind others why they fell in love with statistics in the first place.

References:

  1. http://www.nytimes.com/2009/07/08/sports/baseball/08injuries.html
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