5 Statistics Books You Should Read

Since I’m on a bit of a book list kick at the moment, I thought I’d put together my list of the top 5 stats and critical thinking books people should read if they’re looking to go a bit more in depth with any of these topics.  Here they are, in no particular order:

If you’re looking for….a good overview:
How to Lie with Statistics

This is one of those books that should be given to every high school senior, or maybe even earlier. In fact, I know more than a few people who give this out as a gift. It’s 60 years old, but it still packs a punch. It’s written by a journalist, not a statistician, so it’s definitely for the layperson.

If you’re looking for….something a bit more in depth:
Thinking Statistically

If you want to know how to think about statistical concepts without actually having to do any math, this book is for you. What I would get my philosophy major brother for Christmas so we could actually talk about things I’m interested in for once.

If you’re looking for….something a little more medical:
Bad Science: Quacks, Hacks, and Big Pharma Flacks

Ben Goldacre is a doctor from the UK, so it’s no surprise he focuses mostly on bad interpretations of medical data.  He calls out journalists, popular science writers and all sorts of other folks in the process though, and helps consumers be more educated about what’s really going on.

If you’re looking for….something that will actually help you pass a class:
The Cartoon Guide to Statistics

Not a very advanced class, but a pretty solid re-explaining of stats 101. I keep this one at work and hand it out when people have basic questions or want to brush up on things.

If you’re looking for….a handy guide for those who actually get stats:
Statistical Rules of Thumb

This is one of the few textbooks I actually bought just to have on hand and to flip through for fun. It’s pricey compared to a regular book, but worth it if you’re using statistics a lot and need a in depth reference book. It contains all those “real world” reminders that statisticians can forget if they’re not paying attention. With different sections for basics, observational studies, medicine, etc, and advice like “beware linear models” and “never use a pie chart”, this is my current favorite book.

As always,  further recommendations welcome!

Math Books for Young Kids

After my post of my own new years resolution reading, I thought it might be interesting to follow up with a couple of new books I got my son for Christmas.  He’s 3 and has officially moved from merely being able to recite numbers to actually being able to count objects.  While obviously he’s a bit young for statistics, I want to get him introduced to the world of math and some of the people who inhabit it early. Relatedly, here’s a nifty math skills/developmental chart I found for early childhood.

These are some of the books I’m using:

Bedtime Math: This Time It’s Personal (Bedtime Math Series Book 2)
This one we started using immediately, and it’s quite fun. Basically this is a four book series, created by a mom who realized that while kids get introduced to reading in a fun environment (home, in a parents lap before bed) they get introduced to math in a much less fun setting (later in a classroom). She decided to fix that by putting out books of funny math problems kids could do at home before bed. It has problems for several age groups, starting at around 3. Very fun, and a nice balance for traditional bed time routines.

Curious George Learns to Count from 1 to 100
This one is a big favorite, though we don’t make it quite to 100 yet. Curious George is my son’s hero right now, so I figured I’d use it to encourage him to go further in his counting.

The Boy Who Loved Math: The Improbable Life of Paul Erdos
I’ve mentioned my own obsession with Paul Erdos, and I’m trying to pass it on. Erdos apparently would call children “epsilons”, but Finn doesn’t seem to be taking to that name. This one’s a little long for a 3 year old, but it’s interesting and the illustrations are amazing.

Blockhead: The Life of Fibonacci
This one was recommended to me by my favorite children’s librarian (hi Tracy!). It’s about Fibonacci and is another one that’s slightly too long for a 3 year old, but interesting and historically enlightening. Mathematicians tend to be really fascinating people.

Introductory Calculus For Infants
Because it’s never too early to start.

Experimenting with Babies: 50 Amazing Science Projects You Can Perform on Your Kid
This one’s for mama.

 

 

 

New Year’s Resolution: Book List

Happy New Year!

Man, it’s 2016. Where does the time go?  As we head in to 12 fresh and beautiful new months, I thought I’d take a moment to share the stats/math/science books I plan on reading in the coming year1. Some of these are books I’ve bought and been letting sit, and some are books I plan to get in the near future with the awesome Amazon gift cards I got for Christmas. If I get really ambitious, I may even put up book reviews of some of these when I’m done. I’ve also been toying with doing some sort of master stats/critical thinking book list like the Personal MBA2 list, so please add any suggestions.

January: The Ghost Map: The Story of London’s Most Terrifying Epidemic–and How It Changed Science, Cities, and the Modern World

I’m taking a Epidemiology stats class in January, and this book has been highly recommended by my science teacher brother as a compelling story of how the field got started.

February:The Man Who Loved Only Numbers: The Story of Paul Erdos and the Search for Mathematical Truth

How better to recognize Valentine’s Day than to read a book about a man who loved nothing but numbers? I’ve been a little obsessed with Erdos for a while now (I even got my three year old this book for Christmas), but I haven’t yet read this one.

March: Guesstimation: Solving the World’s Problems on the Back of a Cocktail Napkin

I’ve had this one half finished on my bookshelf for so long they came out with a second edition. I’ll probably just finish the one I have.

April: Understanding Sabermetrics: An Introduction to the Science of Baseball Statistics

Another one that’s been sitting on my shelf for a while….and what better month to read about stats and baseball?

May: What is a p-value anyway? 34 Stories to Help You Actually Understand Statistics

I’m always looking for new ways of explaining stats, and there’s some very cool narrative textbooks out there I’ve got my eye on to improve my repertoire. This is one of them.

June: Beautiful Data: The Stories Behind Elegant Data Solutions

Another one I’ve half finished, but June seems like a good time to read a book about beautiful things.

July: The Signal and the Noise: Why So Many Predictions Fail-but Some Don’t

A Christmas gift from a few years back I’ve severely neglected, but need to read before we actually get to the next election.

August: Teaching Statistics: A Bag of Tricks

I’ve admired Gelman’s work for a while (he has a great website here), and I’d be interested to see how he approaches teaching statistics to students.

September: In Pursuit of the Unknown: 17 Equations That Changed the World

I started this one, but I put this one down because of a busy semester, so I’ll try to get it in right at the beginning. It gives the history of some of the world’s most interesting and useful equations, their development, and how they’ve influenced the world. An interesting historical take on mathematical development.

October: Statistics Done Wrong: The Woefully Complete Guide

Just in time for Halloween, something scary.

November: The Joy of x: A Guided Tour of Math, from One to Infinity

Another interesting looking narrative about math book.

December: The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century

Looks like a fun read for the end of a semester.

 

Any others you’d recommend?

1. All book links are Amazon affiliate links. Glad we had this talk. See ya out there.
2. I love that site, because I really like the idea of getting a somewhat functional education just from books. Obviously no one can become a statistician just from reading books, but most people can get a really good grasp on most of what they need to know. This may be my real resolution for 2016…to get a 99 book list of statistics and math books from different subcategories. So, um, recommendations welcome.

Cool kids and linguistic pragmatism

Yesterday a facebook friend of mine put up an angry post regarding misuse of the word “decimate”.  His chief complaint was that people used it as a synonym for destroy, when really it meant a reduction of 10% or so.  That cleared up the “deci” part of the word for me, but I was surprised that the proper definition was so narrow….so of course I went to dictionary.com to check his facts.

Turns out the “one in ten” definition is specifically marked as obsolete.  The current accepted definition is merely “to destroy a great number of”.  So basically it can’t be used to sub in for obliterate, but the 10% definition was only valid through the year 1600 or so.  Sigh.

I’m not a big fan of people who try to get too cute when picking on the language of others.  While I certainly am irritated by some of the more obvious errors in language (irregardless makes me cringe, and please don’t mix up “less” and “fewer” in my presence), I dislike when people go back several hundred verbal years and then attempt to claim that’s the “proper” way of doing things.  This annoys me enough that my brother bought me this book a few years ago, just to help me out.  I believe language will always be morphing to a certain extent, and while rules are good we just need to accept that all language is pretty much arbitrary.  Thus, I refer to myself as a linguistic pragmatist.  Adhere to the rules, but accept that sometimes society just moves on.

Why am I bringing this up?  Well, after going through that internal rant, I found it very interesting that this study is being reported with the headline “Popular kids who tortured you in high school are now rich“.

Basically, researchers assessed how popular kids were in high school, based on how many people gave you “friendship nominations” and found that those in the top 20% made 10% more money 40 years later than those in the bottom 20%.

Now I think this makes a certain amount of sense.  While the outcast nerd makes good story is appealing, it stands to reason that many of the least popular kids in high school might be unpopular because of real issues with social skills that hurt them later in life (to note, social skill impairment is a co-morbidity with all sorts of things that could make this worse….ADHD, depression, etc).  Conversely of course, those with more friends probably have skills that help them maintain networks later.  Basically, I think this study tells us that the number of friends you have in high school isn’t totally random.

My issues with the reporting/reading of this study is in the semantics.  I think there’s a disconnect between our common interpretation of “popular in high school” and the actual definition of “popular in high school”.  The researchers in this study weren’t assessing the kids other kids aspired to be, they were assessing the kids who actually had lots of friends and were well liked.  While the classic football player who beats up kids in the locker room may get referred to as a popular kid, it’s likely he would not have had many people naming him as a friend on a survey.  So basically, the study had a built in control for those kids who were temporarily at the top of the social ladder, but lacked actual getting along with people skills.  I had an incredibly small high school class (<30) and I could name several kids who fell in the "perceived popular" category but not the "actually popular" category.

All this to come back to my original point.  Words mean different things depending on context, and this should always be taken in to account when assessing research and reading subsequent report.  It’s not bad data, just a different set of definitions.

5 Easy Pieces

Simply Statistics put up this link to an interview with David Spiegelhalter on 5 good books to help understand statistics and risk.  I haven’t read any of them, but they looked excellent.  Also, this quote is excellent:

There is a nice quote from Joel Best that “all statistics are social products, the results of people’s efforts”. He says you should always ask, “Why was this statistic created?” Certainly statistics are constructed from things that people have chosen to measure and define, and the numbers that come out of those studies often take on a life of their own.

I’m pretty sure that about sums it up.

Book Recommendation – How to Lie With Statistics

If one has free reading time or just really likes lists (and boy do I love a good list!) the Personal MBA reading list is pretty darn cool.  It claims to give you knowledge equivalent to an MBA in 99 books, without any of the crippling debt.  I’m about 10 books in, and there’s some really great stuff on data, statistics, analysis and presentation.

One of the classics of course is How to Lie With Statistics.  It’s a great book, easy reading, though the examples are outdated to the point of near distraction (salaries list at $8000/year, that sort of thing).  Still, clear and concise, and shows you that bad data has been around for quite some time.

One of my favorite moments is when he goes after Joseph Stalin for his bad data….in retrospect that kind of feels like saying Hitler was a bad dresser.  Still, pretty interesting to see where the misinformation starts.  This book should be required reading for everyone.