Posts Tagged ‘ Business ’

Shaking up expectations for pension benefits

May 20, 2015
By
Shaking up expectations for pension benefits

Ted Ballachine wrote me about his website Pension360 pointing me to a recent attempt at visualizing pension benefits in various retirement systems in the state of Illinois. The link to the blog post is here. One of the things they...

Read more »

Deflategate 3: nature of evidence

May 7, 2015
By
Deflategate 3: nature of evidence

Last time we heard about Deflategate on this blog, Warren Sharp compiled some statistics on fumble rates, showing that the Patriots were unusually good at avoiding fumbles. (link, link) I thought the level of analysis was "above average" and remarked that statistical evidence of this type can only get you so far. The metric is indirect, and it does not speak to causation. The official investigators have now issued their…

Read more »

Story time, known unknowns and the endowment effect in an HBR article on customer data

May 6, 2015
By
Story time, known unknowns and the endowment effect in an HBR article on customer data

Harvard Business Review devotes a long article to customer data privacy in the May issue (link). The article raises important issues, such as the low degree of knowledge about what data are being collected and traded, the value people place on their data privacy, and so on. In a separate post, I will discuss why I don't think the recommendations issued by the authors will resolve the issues they raised.…

Read more »

Painting the full picture of the employment situation

May 5, 2015
By
Painting the full picture of the employment situation

It's very frustrating to read the mainstream articles about the recent unemployment report. For example, the New York Times said "U.S. Jobless Claims Hit 15-year Low." (link) At this point, everyone should be aware of how employment statistics, in particular,...

Read more »

Reading between the gridlines

April 28, 2015
By
Reading between the gridlines

Reader Jamie H. pointed me to the following chart in the Guardian (link), which originated from Spotify. This chart is likely inspired by the Arctic ice cover chart discussed here last year (link): Spotify calls its chart "the Coolness Spiral...

Read more »

More on the AA paper

April 21, 2015
By
More on the AA paper

This is a supplement to the previous post about a new research paper on the effect of Alcoholics Anonymous, and an NY Times exposition that I commented on. A misreading of that article led me to complain about per-protocol analysis, which wasn't the methodology behind the Humphrey et. al. research. I will explain their methodology in this post (known as instrumental variables analysis). *** In the last post, I showed…

Read more »

NYT likes new AA study. Why I am not convinced.

April 20, 2015
By
NYT likes new AA study. Why I am not convinced.

[After communicating with Frakt, Humphrey and Dean Eckles, I realize that I was confused about Frakt's description of the Humphrey paper, which does not perform PP analysis. So when reading this post, consider it a discussion of ITT versus PP analysis. I will post about Humphrey's methodology separately.] The New York Times plugged a study of the effectiveness of Alcoholics Anonymous (AA) (link). The author (Austin Frakt) used this occasion…

Read more »

Hello to St. Louis readers

April 15, 2015
By
Hello to St. Louis readers

I'll be hosting a Data Visualization workshop at the Digital Media Marketing Conference in St. Louis, Missouri on Thursday. Here is the link to their website. The workshop is arranged from three themes: Appreciating, Conceptualizing, and Improving. There will be...

Read more »

Planned redundancy

April 7, 2015
By
Planned redundancy

The following Wall Street Journal caught my eye the other day: (Link to article) Looking closely, I realize that the four charts are identical, except for the call-outs. This is a kind of small-multiples in which the same data reside...

Read more »

What popular baby names teach us about data analytics

April 6, 2015
By

In my latest piece for Harvard Business Review (link), I tackle this common problem in the interactions between data scientists and business managers: A typical big data analysis goes like this: First, a data scientist finds some obscure data accumulating in a server. Next, he or she spends days or weeks slicing and dicing the numbers, eventually stumbling upon some unusual insights. Then, a meeting is organized to present the…

Read more »


Subscribe

Email:

  Subscribe