## Wednesday, May 31, 2006

## Sunday, April 30, 2006

## Thursday, April 20, 2006

### CONNED

**CONNED AGAIN, WATSON: CAUTIONARY TALES OF LOGIC, MATH AND PROBABILITY**by

**Colin Bruce**

Guess we know who got

**"conned"**this time. ...but you get the idea... :)

## Tuesday, April 18, 2006

### If Statistics Lie, Can Deceive, and Can't Be Trusted, then Why Can't Santa Claus Be Real?

Here's an interesting article on the statistical basis for a

**"real"**Santa:

http://www.funs.co.uk/fs/s8.html

and one on the nonstatistical basis for a **fictional** one:

http://en.wikipedia.org/wiki/Santa_Claus

**YOU DECIDE!**

### Watchwords to Look Out for When People Are Trying to Get You Interested in Statistics

**Risk**(Examples that go along with this often involve stories about money or references to investments)

**Chance**(Alot of Science Stuff and stuff designed to appeal to the "Discovery Channel Watcher" in all of us, uses this word).

**"Deception" "Lies" "See Through"**or "

**Fool"**. Basically, these books are designed to teach regular people how to understand statistics without making stupid mistakes, especially when (as is often totally unnecessary, since most people already have such poor statistical intuition anyway), someone is trying to manipulate the way in which the statistical data is presented.

**Coins**(Usually Being Flipped),

**Cards**, or

**"if, then, well then what are the chances of both or none or some"**type of examples (Look in any statistics textbook and you'll immediately see what I am talking about, if you don't already).

### Subgenres of Type Two

**CASH**(i.e., not Johnny, although the movie was great, but rather portfolio theory, financial derivatives, investment planning, and all that kind of cool stuff)

**SCIENCE**or

**THE HISTORY OF SCIENCE**

**PRACTICAL THINGS**(Other than making cash, which is covered by type 1) This might include diverse areas such as

*gambling*, social science stuff, or busienss statistics (other than stuff dealing strictly with finance such as portfolio theory and financial derivative stuff which is covered under type 1) in areas such as marketing research, manufacturing reports, and organizational behavior metrics.

### THIS IS TO SEE IF YOU'RE PAYING ATTENTION!!!

Cars, Blondes, What?...Whatever.... To all you SEAS (School of Engineering and Applied Science) guys out there, wannabe SEAS guys, and of course, our pure math-stat buddies out there, before we got into the "Sub-genre Taxonomy" stuff, I thought you could use... well, you're smart,... YOU FIGURE IT OUT... :)

### Subgenres - the DEFINITIVE GUIDE

*i.e. a bookstore without textbooks*). Well now, I am going to talk to you about subgenres WITHIN those three types. Instead of bombarding you with a taxonomy chart like they do in Intro. to Biology class (or for those of you who paid attention in your college stat. classes - your first two years of Medical School), instead I'm going to give it you a piece at time.

This also fits in with our aforementioned:

**(THE SUSPENSE IS BUILDING)**

### I Know What You Did LAST SUMMER, and It Suck*d!

The link is right here:

http://www.ce.columbia.edu/summer/

For High School Students, You Might Want to Go To:

http://www.ce.columbia.edu/hs/

The Courses Offered in Statistics are:

http://www.ce.columbia.edu/summer/statistics.cfm

Obviously, these are not the only courses that require statistics, but they are the ones offered by the department. The mathematics courses are listed under the following link:

http://www.ce.columbia.edu/summer/math.cfm

### Blondes, Car Accidents, and Intelligence

Do Blondes Have More Fun? Are They Stupid and Hot, or...well,... Just Hot? Are they part of an Aryan "Masterrace"? I don't have any definative answers for you guys (and gals) out there, just yet (we might revisit this topic at some later date, since who doesn't like revisiting a few blondes if they're hot?), but I did run across this article from a few years back.

http://www.smh.com.au/articles/2003/11/30/1070127270286.html?from=storyrhs

### I've Heard They Make Big Bucks, ...but REALLY, ...How Do I Become an Actuary?... and Why Would I Want To (Besides the Cash)?

*read we're never going to run out of stuff to talk about regarding actuaries on a probability and statistics weblog-magazine, duh...*).

### Interviews...they're coming...! :0

**important**people who are

**currently**doing some

**important**stuff with statistics, and have them answer questions about themselves and their work we think you will find

**important**. Stay tuned..., it's,... you guessed it,...

**IMPORTANT**.

## Monday, April 17, 2006

### Are the People Who Write These Books Promoting a Culture of "Statistical Literacy" or Are They Just Making Money by Saying It's O.K. to be Stupid?

**three**categories.

**have**to take. The content of these books is often good, comprehensive given the size of these "get-through" guides, and very frequently if you actually use the books the way they were intended, you'll know a hell of a lot of statistics.

*"See Mom, I can be a scientist, too,"*type of books. Basically, these are books that appeal the "Reading Rainbow" watcher in all of us. Remember when you were little and actually good at science? Remember how you use to come home from school and be all excited about growing a plant out of a potato in a jar or talking about the local weatherman who came to your school and talked about why clouds fill up with moisture and rain? Well, anyway these books are written in the same vein. They often try to answer the question, "What's new and interesting in statistics?", or "Why is statistics interesting to people only interested in things which affect 'the real world'?". Anyway, these books are often light on the actual instruction of statistical techniques and heavy on anecdotes. They allow a reader to be able to talk about statistics as if they knew how to do the problems, and maybe even fake the fact that they know a lot about the field. Basically, these books help a

**wantabe**"smart guy" fake it.

**anticipate a negative**. The phrase, "anticipate a negative" is a phrase a lawyer friend of mine once used to describe to me the process of mentioning something negative you know the person who you are speaking with (

*read cross-examining attorney*) is going to bring up, and making sure you get it out there preemptively (

*read first*) and packaged with as much positive spin as you can muster. This way, when the inevitable comes out, it doesn't seem that bad, and it doesn't seem to any third party observers (

*read jury*) that you were trying to hide something embarassing by not mentioning it yourself. These books do something similar and will try to win you over by acknowledging that statistics is boring or hard, and then after they've got you thinking that they're on your side and they understand what you're going through, they promise to teach it to you nice and easy. These books make good general overviews, but often times don't teach you very much substantively, either about how to do statistics problems or what interesting stuff going on the field of statistical science makes learning the techniques worth one's time. In other words, don't pick one of these book up if you're preparing for an AP Exam or getting ready to impress a people at a dinner party.

**"statistics suck!"**,

**it can be**

**explained easily**

**if**one of these "genius authors"

**talks down to one enough**, and that

**after it has been explained**to an "idoit, "or a "dummy," or "demystified, "well, then pretty much

**that's all you're supposed to know**and

**all you can know**.

**interesting (now there's a concept)**things and which could overtime make a difference in how motivated the mainstream public is to become "statistically literate,"

**the opposite is done, and the opposite effect achieved!**

## Wednesday, April 12, 2006

### So it's the Middle of April and You Need to Cram?

**FAST**! The problem is that every year there seem to be more and more books to choose from and almost no way to compare them to one another. You might flip through one or two, but how do know which one will really be the best bang for your, not buck, but time.

Well, next month we're going to be trying to get some feedback posted from people who've used the various "helping" books either for the AP or Finals. We'll then try to either rank them or at least describe the main ones (Barron's, Kaplan, Princeton Review, Sparknotes, etc.)in Math/Statistics.

Since this online blog/magazine didn't exist last year, we don't have a winner to sight from last year's nonexistant rankings/polls. So like so many publisher/editor-and-chief's before me, I'll just pick the one that seems to work for me. I wonder if Hef had the same problem with Marilyn Monroe? Anyway, and the winner is...

THE PRINCETON REVIEW - PERIOD. And no, that's not Marilyn Monroe on the cover.:(

### Did Statistical Science Win World War 2?

*Intelligence In War*, back in 2003, which apparently he has updated in 2004. In it, he talks about the importance of mathematics and statistics in estimating the likely probability that certain signals meant certain letters or numbers in a code, and what a contribution mathematicians from England, Poland, and the United States made to breaking the supposedly unbreakable "Enigma" code of the Germans at places like Bletchley Park (a mansion in England where mathematicians would work on the problems posed by German encryption). John Keegan points out that unlike today where knowledge of foreign languages is often the key to breaking the code of terrorists, the ability to break the German encryption codes was due entirely to mathematics and the effective use of probability theory applied to vast quantities of recorded German messages sent in code.

### A Victor, Not a Butcher - Statistics, A Scorecard for Life?

*A Victor, Not a Butcher: Ulysses S. Grant's Overlooked Military Genius*, about... you guessed it, Ulysses S. Grant. Basically, the book said that unlike his reputation as a general who needlessly squandered lives in order to make up for his lack of strategic skill (especially compared to the venerable and brilliant Robert E. Lee), Grant had lower losses in terms of the percentage of his overall number of his troops killed than did Robert E. Lee, and that people who characterized Grant as a butcher (after the war) only did so to satisfy the pride of resentful Southerners.

Without going into a high school history class walk down memory lane, the thing that struck me was how statistics are almost always invariably used as the standard for judging whether something subjective and theoretical is in fact objective and real...like this theory about Grant being a butcher.

Is/Are Statistics the Scorecard for life? What are the implications for this in a data rich society and information based economy? ...Stay tuned and find out.