Data is the New Hot, Drop-dead Gorgeous Field

Posted to Statistics  |  Nathan Yau

We all know this already, but it’s nice to get some backing from The New York Times every now and then. In this NYT article, that I’m sure has spread to every statistician’s email inbox by now, Steve Lohr describes the dead sexy that is statistics:

The rising stature of statisticians, who can earn $125,000 at top companies in their first year after getting a doctorate, is a byproduct of the recent explosion of digital data. In field after field, computing and the Web are creating new realms of data to explore sensor signals, surveillance tapes, social network chatter, public records and more. And the digital data surge only promises to accelerate, rising fivefold by 2012, according to a projection by IDC, a research firm.

I’ve got about one more year (hopefully) until I finish graduate school. Hmm, things are looking up, yeah? Of course, it’s never been about the money. The profession of statistician didn’t nearly seem so hot when I started school. The best news here is that us data folk are going to get paid for doing what we enjoy, and as time goes on there’s only going to be more data to play with, and we’re going to be in high demand:

Yet data is merely the raw material of knowledge. “We’re rapidly entering a world where everything can be monitored and measured,” said Erik Brynjolfsson, an economist and director of the Massachusetts Institute of Technology’s Center for Digital Business. “But the big problem is going to be the ability of humans to use, analyze and make sense of the data.”

Wait, but it’s not just statisticians who can interpret data:

Though at the fore, statisticians are only a small part of an army of experts using modern statistical techniques for data analysis. Computing and numerical skills, experts say, matter far more than degrees. So the new data sleuths come from backgrounds like economics, computer science and mathematics.

Like a… data scientist? Excellent.


  • This latest round of pro-statistician articles have me excited too. I’ve been toying with the idea of double majoring in statistics and it’s looking like a better idea every day.

  • It goes a bit against the argument in books like “A Whole New Mind” that right brainers will take over the world from left brainers…

  • Analytical chemists have been dealing with data for a long time – even before computers. We were using strip chart recorders then. One of the benefits I see there is that we have standard ways of presenting the data which can make interpretation easier. I know an infra-red spectrum when I see it, just from how the data is presented or a mass spectrum. I don’t have to invest effort anymore in trying to understand the visualization approach.

    A weakness I see in presenting data from other sources is that there are no standards and it often takes quite a bit of effort just to understand how the data is presented before one can even start considering what the data shows. Some of that may be the newness of the data source/presentation and once people recognize good visualization approaches, they will start to “standardize”.

    While there is certainly room for a new and innovative visualization, some standardization would be beneficial.

  • The stealthiness of the social data scientist field is surprising, especially since we elected a Community Organizer as president. Combine wonkishness and data scientist skills… ahhhh… the possibilities….

  • @jan —
    Perhaps not surprisingly, I think these stories confirm the argument. Computers do the heavy number-crunching — leaving humans to recognize patterns and interpret the data. These folks must have a good left brain, of course. But the differentiator is the right-brain — the ability to connect the dots, make new associations, and detect trends. In other words, these statisticians need, er, a whole new mind.
    Dan Pink

  • Daniel –

    If I am understanding you correctly, you must have a very limited view of what a statistician is. Data analysis is iterative – you do some “number crunching”, or as I like to call it, modeling – and then you use visual diagnostics to see how you are doing. Then you make adjustments and iterate. This requires a strong right and left brain, and this is something that statisticians have been doing for a very long time. To think of statisticians as people with a weak right-brain is quite naive.

    • I think we’re making the same point, actually, no?

      • Possibly – it depends on what you meant when you wrote “statisticians need a whole new mind”. The way I interpreted it is that you think that statisticians currently don’t have this “whole new mind”. In that case, I am trying to correct you – a good portion do. Perhaps what you meant was that statisticians had better be sure that they do have this mind. In that case, yes, we are making the same point.

  • Nathan,

    Do you have any suggestions for schools / programs that are well known for their BI / Statistics curriculum, especially in the NYC / N.E. US area?

    I keep flirting with the idea of going back to school, but every program I’ve looked at seemed to be incomplete in one way or another.

    I keep hoping that you’ll make a post (or maybe this is a better forum topic) about this.


One Dataset, Visualized 25 Ways

“Let the data speak” they say. But what happens when the data rambles on and on?

A Day in the Life of Americans

I wanted to see how daily patterns emerge at the individual level and how a person’s entire day plays out. So I simulated 1,000 of them.

Best Data Visualization Projects of 2016

Here are my favorites for the year.

Causes of Death

There are many ways to die. Cancer. Infection. Mental. External. This is how different groups of people died over the past 10 years, visualized by age.