I'm late in linking to this positive review of the book from Robert Kosara, who writes the EagerEyes blog. I love this review because it's one that truly gets the concept of the book. Kosara's blog is a great read too.
On Wednesday, I'll be at the Princeton Library at 7:30 pm to meet readers. Note that this is the township library, not the university library. Hope to see some of you there.
On the right panel of this blog, I have been putting information about my upcoming book-related events.
The next one is at the NYU Bobst Library on Tuesday 6-7 pm. (It is a repeat of a talk I gave last week at the same venue, which was very well received.) I'll be signing books.
On Wednesday at noon, I'll be the presenter at the INFORMS NYC chapter luncheon. The announcement is found here. The talk will cover what I consider to be the next key challenge in business analytics. It is similar to the plenary talk I gave at the JMP Discovery Summit last month.
I have been involved in the INFORMS NYC chapter for a few years, and we have a solid group of practitioners who meet monthly, and always have great discussion, so I'm looking forward to this talk. Take a look at our past luncheon topics.
Numbers Rule Your World was picked by Fareed Zakaria on CNN as Book of the Week on Sept 5. His verdict: "For those of you who hated statistics in college, this is actually an easy read with a big benefit." Thank you Fareed.
I gave a plenary talk on "What happens after the math is done?" at the JMP Discovery Summit in Cary, NC on Sep 15. (The abstract was posted here.) Dan Ariely (Predictably Irrational) also spoke at the conference about his new book.
Daniel at the Firefly Ecometrics blog summarized part of my talk and gave his reactions to it.
One insight I gained from the conference is that even long-time Junk Charts readers are unaware of this sister blog! I think this is because the RSS feeds are separate. (The Twitter feed though is the same.) Will try to rectify this soon. As I mentioned in my talk, the two blogs are synergistic: one is about visual communications, the other written communications.
I noticed two new reviews of the book.
One is by Professor Gary Fetter at Western Carolina University's Business School, published by Asheville Citizen-Times (link here). He rated it 4/4, with the following summary comment: "In 'Numbers Rule Your World,' Fung makes statistics entertaining, accessible and relevant to our lives."
Another is on Martin's blog. He uses the occasion to point out the truism that "data is not the same as information", which is the first principle I teach to my students. The arrival of computer technology -- the plunging cost of storage and the fast growth in processing power in particular -- creates a huge amount of data, much of which were designed for engineering purposes. The existence of data does not per se make them useful. Martin gives the example of plotting the frequency of Facebook messages containing the word "break-up" and asks, essentially, "what happens after the math is done?"
That is the title of my talk to be delivered next week at the JMP Discovery Summit (Sep 15 at 10:15 in Cary, NC). The other talks look great too, including Dan Ariely and Dick De Veaux.
Here is the abstract I submitted:
The phenomenal recent success of the Freakonomics and Gladwell franchises, and their offshoots, has
sparked unprecedented curiosity in the analytics profession. Not long ago,
business executives tended to see us as technocrats speaking an abstruse lingo
engaged in niche activities with uncertain effects: smart, intimidating, hard
to grasp, lost in details.
Times are changing. The famous authors have demonstrated how
to use low-density, soft-touch narratives to convey analytical results to broad
audiences. They imagine the analytics professional as a kind of intellectual
hero, wielding data as weapons against conventional wisdom. The common
structure of these stories follows the well-known analytical process, beginning
with defining the research question, and ending with discovering the correct
All this is masterfully told, but represents only half the
story. In my experience, the analytics job is less a solitary struggle for the
scientific truth than a managerial challenge in balancing objectives,
facilitating collaboration, and creating consensus. In this talk, I will tell
the second half of the story, using materials from my recently published
book,Numbers Rule Your World. The focus is on what happens after the
math is done.
For those who couldn't attend, I summarize the discussions that took place during the JSM session, and the talk at EdLab at Columbia's Teachers' College.
At JSM, the panel, led by Professor Mammo Woldie, focused on what business analytics is all about. Dan Coates, who heads up Youth Pulse and previously spent years at SPSS, gave an overview of the types of problems that businesses face, and the companies that have made key investments in developing advanced analytics teams. Nathaniel Derby, an independent consultant and entrepreneur, has lots of advice for statisticians who are interested in developing private practice. I made some comments about how to recruit and manage an analytics team.
Several themes emerged that elicited considerable discussion. One revolves around the analogy to cars. Should schools teach students how to drive a car or how to build a car? My view is that today, almost all statistics courses teach building, and if there is excess time (however scarce), may cover a tip or two on driving (like, pay attention to the cyclists). For most people in business it is not necessary to know how to build a car but essential to understand how to drive one.
This leads to a related point. The decision makers at most corporations are not quantitative thinkers. Is it better to give corporate executives technical training so they understand what statisticians are saying? Or is it better to train statisticians to speak to non-technical people instead? Readers of my blogs won't need to ask where I stand on this. Unfortunately, I sense that outside of this room, my opinion is not in the majority.
PS. An attendee who works at Capital One pointed out that their business leaders typically have quantitative training, and would demand technical details. Those are the cultures that would be most comfortable for statisticians but today are exceptions rather than the rule.
One of my slides received much attention. Nathaniel first asked for it to be re-posted, and it stayed up there for much of the session. The slide points out that analytics professionals do best if they can succeed on three types of skills: technical (obviously), business thinking and "intangibles". Business thinking is often the hardest to develop because quantitative training in college or grad school (outside of business schools) just do not teach it. For me, intangibles are the hardest to find, mainly because it is impossible to gauge in an interview.
Another theme concerns which types of companies are investing in analytics. In his career, Dan has sold analytical solutions to many companies and he told us that only large corporations have the resources to do so. I am sympathetic to this point of view because analytics has prerequisites, the most obvious being an accessible, somewhat accurate database. Nathaniel, however, has been working with many small companies, so what Dan and I see as a gap he sees as opportunities.
EdLab at Teachers' College does a lot of interesting things, like creating technologies for the classroom and libraries, blogging, and analyzing data sets in the education sector. I had a great time speaking to this group, which included summer interns (hello, the one who asked about the difference between observational study and experimental study, perhaps working on a problem set?).
The most intriguing and unexpected question was: to do well in this business, do you have to read a lot? This is where I stumbled into a spaghetti carbonara analogy while mixing metaphors with the gray flannel, with which I have already been associated. Basically, statistics is not pure mathematics, there is not one correct way of doing things, there are many different methodologies, like there are hundreds of recipes for making carbonara. What statisticians do is to try many different recipes (methods), and based on tasting the food (evaluating the outcomes), we determine which recipe to use. Because of this, statisticians need to be well-read, to keep up with what are the new methods being developed.
Another attendee -- a reader of Junk Charts -- asked about why I prefer graphics that are clearer but less "engaging" than the original. By "engaging", he meant telling stories. This gives me an opening to point out that while I have written extensively about the shortcomings of "infographics", one aspect I like a lot is the use of narrative in this type of charts, the use of multiple charts to illustrate complex concepts. Like going from photographs to a movie.
For those in the New York area, I will be giving a talk tomorrow (Aug 11, Wed) at noon at Columbia's EdLab. The talk will cover a topic from the book, and what about it is not typically discussed in statistics courses. See here for an abstract.
Blogging will resume after the holiday weekend. In the meantime, check out these photos from the book signing at Book Expo America (BEA) last week. The publisher set up a fun spinning wheel game as people lined up to get autographs. The books were snapped up in about a half hour, much to our surprise but a pleasant one. Some love numbers while many others know people who love numbers.
A few more reviews of the book by bloggers have trickled in, thankfully all positive.
From Claus at planetwater, a blog about "ground water, engineering, science, geo-statistics":
I really loved reading those stories. They are well written, I think
well understandable for somebody who is not experienced or even trained
in “statistical thinking”. Finally, a big plus is a longer than normal
“conclusions” section, where Kaiser Fung tries to put the underlying
basic thoughts of each story into almost all the other stories’ context.
See also Claus's post on "Magnitudes of Extreme Weather Events", which is his response to a topic in my book.
I really don’t do book reviews, but this is an exception. And I’m still in the middle of reading it, too... For folks who have inquisitive minds about why stuff is there and what
happens, I suggest reading Fung’s book, which was recommended by a
friend who also seems to be into understanding innocuous bits of
This is one of the best books I have ever read next to Freakonomics by Steven Levitt and Stephen Dubner... This book has opened my eyes to many more ideas of what may be behind
my thoughts and it will help me think rationally according to
statistics when making a decision in the future.
Originally heard of this from reading Tom Peter's Twitter
feed and it is well worth your time. Everyone instinctively knows the
role of numbers in your life, but here you can delve deeper and get a
much greater understanding which could change the way you live.
Seriously. Check it out.
In addition to the Japanese version, Numbers Rule Your World will be coming out in Chinese and Korean.
Since I have many European readers, I hope they will translate it to French, German, Spanish, Italian, etc.
Clive Thompson tells Wired readers that we should all speak the language of data. (The online version is here. The article also appears in the May issue.) He argues that statistical illiteracy is the nation's political problem. "If you don't understand statistics, you don't know what's going on -- and you can't tell when you're being lied to."
In other words, everyone should think like a statistician... my pitch to the Baltimore Sun reporter is here.
As happens with these interviews, a great deal was said, much of it vanished during the editing process.
The example I provided illustrates "survivorship bias". The most important metric for the retail sector is same-store sales growth, the average change in sales experienced by individual stores. Less known is the fact that only stores opened for at least one year are considered eligible for the sample: this is sensible since new stores may experience "growing pains" and thus unfairly drag the metric down.
Even less known is the fact that stores closed during the reporting period are excluded: this is sensible in a stable economy; removing transient activity can be justified if one wants to measure the average trend. In a recessionary environment, such an exclusion creates a bias in the sample, which has the effect of magically creating sales growth when sales is merely migrated from one store to another.
Imagine there are four Starbucks in your neighborhood (quite likely in NYC). Starbucks decided to shut one of the (low-performing) stores down. Because this store was not reported as open at the end of the month, it was deemed ineligible for the sample. Meanwhile, all the customers of this store took their business to the other three Starbucks in the neighborhood. Those three stores saw a jump in sales. The jump in sales constituted same-store sales growth, when in fact they merely migrated from the closed store.
It's a form of "survivorship bias" because the sample used to estimate same-store sales selectively included only "survivors". If the closed store were also added to the sample, then the drop in sales (to zero) at this store would cancel out the jump in sales in the other three stores, which would reflect the economic reality.
So, yes statistics is tricky but it can be learned.
Thanks, Clive, for devoting a column to make this important point.