Post 31

Post 31

Post 30

Post 29

Post 28

Post 27

Post 26

Post 25

Post 25

Post 24

Post 23

Post 22

Post 21

Post 20

Post 19

Post 18

Post 17

Post 16

Post 15

Post 14

Post 14

Post 13

Post 13

Post 12

Post 12

Post 11

Post 11

Post 10

Post 10

Post 9

Post 9

Post 8

Post 8

Post 7

Post 7

Post 6

Post 6

Post 5

Post 5

Post 4

Post 4

Post 3

Post 3

Post 2

Post 2

Post 1

Post 1

post 29

post 30

post 28

post 27

post 28

post 27

post 26

post 25

post 24

post 23

post 22

CONNED

Just after you giving you the some watchwords to look out for when browsing for books, we came across a perfect example of what we were talking about that didn't use any of them:

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... :)

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

Since we're going to start doing book reviews soon, I thought I'd give you a few give you a few things to look out for, if you decide to browse on your own in a library or bookstore instead of, or in addition, to reading the books that we feature or recommend. Plus, after reading this list, you might just spontaneously burst out laughing when your high school teacher, TA or Prof. decides to make "statistics interesting" by using some of these canned items. And you thought recycling was only for bottles.

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

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

*Note of the use of the phrase "Discovery Channel Watcher": I realized "Reading Rainbow" watcher made me sound dated, ...sorry Levar.

3. Numbers in combination with the words or variations of the words: "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.

4. Examples or stories involving: 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

Could there be a more boring title than that? Well, hey guys, we gave you a nice pic of Veronica Varekova last time, so now it's time for us to get even (for those of you who are gay men, straight women, or other people for whom Veronica Varekova doesn't really do anything for you, ...except maybe make you feel little fat or jealous, ...don't worry,... we'll find something for you in our next attention grabbing stunt - designed to keep you reading our magazine-blog, that'll make straight men, bisexual, and lesbian women feel just as badly:) ).

Basically, the subgenres are:

1. The type that talk about 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)

2. The type that talk about SCIENCE or THE HISTORY OF SCIENCE

3. The type that deal with so-called 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

O.K., so you saw how I definatively,... yes, DEFINATELY DEFINATIVELY,... defined the 3 TYPES of statistics books you're likely to find in your local, non-university bookstore (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)

So You Noticed The Snow in the Pictures?

Does it snow at Columbia in the middle of summer? Well, ...in a word...NO! But there's a reason why we used those pictures, and it's not "to see if you were paying attention".

(THE SUSPENSE IS BUILDING)

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

Hey everyone, did you know Columbia runs a summer session, in fact, two of them to be more precise.

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)?

If you've ever visit a public place where people study (public library, coffeeshop, bookstore, etc.) frequently, you're eventually going to run into somebody studying for the actuarial science exams. There are a lot of them, and most of the people who take them, end up working for years, while studying for each one. Plus, get this, the exams are offered only once a year. Once you're done though, since a lot of people don't make it, you're pretty much set, or so I've heard. Below are a few links you might want to look at just to get an idea of what's involved. Don't worry, we're going to revisiting the wonderful world of actuaries many, many times before we give it up (read we're never going to run out of stuff to talk about regarding actuaries on a probability and statistics weblog-magazine, duh...).

http://www.beanactuary.org/

http://www.actuary.com/

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

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

Need I say more. Watch out!... We're going to be doing some interviews soon with some 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.

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?

Look, I know the phrasing of the title is wordy, a mouthful, and maybe a little awkward. In case you didn't notice, this is not the probability and diagraming sentences website/magazine/blog/stop trying to define a twenty-first century medium in terms of twentieth century vocab anyway, ...O.K.?!

If you go to any non-university bookstore and head to the statistics or math section, you'll probably see books that fall into three categories.

The first are the books that are designed to help you prepare/practice for tests, exams, and basically pass courses the authors assume you 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.

The second category of books is what I would call the "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.

Finally, there's the last category of books, and intuitively, I'm going to assume the best selling. Basically, these books are books which try to do what people in sales have been doing for years, or witnesses about to be cross-examined have been trained to do... 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.

My personal feeling is that the wide range of books that market to people on the basis of not making people cry, while doing statistics (there really is a book like this, I kid you not), or feel pain (there really is one like this too), or market to them based on the implied fact that the subject is hard and that they are dumb (there are a bunch of them that do this), not only in the long run doesn't teach people much, because the books themselves are so shallow, but also inculcates in them a mood which the statistical profession has for years tried to change - basically, that "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.

Instead, of casting statistics in a positive light and explaining it "simply" with the implicit assumption that someone will want to learn it well, so they can do all sorts of 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!

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

Yup, it's that time again - when the weather gets better and finals come closer. Have you got an AP Exam in Statistics you convinced your parents to blow almost 100 bucks on, or a final in college the first or second week of May (like most students do at Columbia)? Well, if you do, you might just have walked into your nearest bookstore searching for some book that'll help you cover all the important stuff and 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?

John Keegan, the famous military historian, wrote an interesting book, 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?

I was in Borders the other day and I saw the book, 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.