Editor’s Note: This post written by Roger Peng and Jeff Leek. A couple of weeks ago, we announced that we would be teaching free courses in Computing for Data Analysis and Data Analysis on the Coursera platform. At the same time, a number of ot...
Editor’s Note: This post written by Roger Peng and Jeff Leek. A couple of weeks ago, we announced that we would be teaching free courses in Computing for Data Analysis and Data Analysis on the Coursera platform. At the same time, a number of ot...
In his 2004 paper in Trends in Ecology and Evolution, Steven Peck argues: Simulation models can be used to mimic complex systems, but unlike nature, can be manipulated in ways that would be impossible, too costly or unethical to do in natural systems. Simulation can add to theory development and testing, can offer hypotheses about the
When linking to my review of Duncan Watts’s book in a recent post, I came across some fun bits that I’d like to share (for those of you who didn’t just click through and read the whole thing): On business books: I’m not so interested in the business angle but I suppose that’s how you [...]
Ezra Klein (link) cited a particularly revealing graphic from the Hamilton Project. And I found this via Washington's blog (link). The gist of the story is that most reports citing median annual earnings of US workers fail to disclose a severe selection bias: the number reflects the median of full-time wage earners. The number cited is the black line in the chart to the left. The more realistic number is…
In a previous post I showed that it's more intuitive to think of a gamma distribution in terms of its mode and standard deviation (sd) than its mean and sd because the gamma distribution is typically skewed. But I did not show how to estimate the mode ...
The Olympics are a big deal on a global scale. How big? Perhaps Paula Radcliffe (an English long distance runner) said it best: "I have achieved a lot and I'm grateful for that - I'm just a bit greedy because I want to add the Olympics. It's...
How Many Data Scientists Are There?I've seen a lot of articles lately about “Big Data” and the looming “talent gap.” This article from the Wall Street Journal is a good example. It cites a McKinsey estimate that states that we will need 1.5 m...
A few years ago I stumbled across a blog post that described a person’s complete cv. The idea was that the cv listed both the things they had accomplished and the things they had failed to accomplish. At the time, it really helped me to see that ...
What's the one thing we need to do?Marketing researchers are asked this question frequently whenever they analyze customer satisfaction data. A company wishing to increase sales or limit churn wants to focus only on the most important determ...
Like some of the other terms in our list--level and beta--GLM has two different meanings. It's a little different than the others, though, because it's an abbreviation for two different terms: General Linear Model and Generalized Linear Model. It's extra confusing because their names are so similar on top of having the same abbreviation.
Solomon Hsiang writes: One of my colleagues suggested that I send you this very short note that I wrote on a new approach for displaying regression result uncertainty (attached). It’s very simple, and I’ve found it effective in one of my papers where I actually use it, but if you have a chance to glance [...]
I’ve been interviewed twice in the last year: For DecisionStats, 9 August 2012. For Data Mining Research, 21 October 2011. Republished in Amstat News, 1 December 2011. Some readers of this blog might find them interesting. I said a few things in t...
I've seen analyses of Fisher's iris data so often that sometimes I feel like I can smell the flowers' scent. However, yesterday I stumbled upon an analysis that I hadn't seen before. The typical analysis is shown in the documentation for the CANDISC procedure in the SAS/STAT documentation. A (canonical) [...]
If you find this blog helpful (or even if you don’t but you’re interested in blogs on research issues and tools), there are a few other blogs about doing research that you might find useful. Here are a few that I read. Patter — Pat Thomson. The ...
Our first outgrowth of “Deconstructing Larry Wasserman”. Aris Spanos – Comments on: “Low Assumptions, High Dimensions” (2011) by Larry Wasserman* I’m happy to play devil’s advocate in commenting on Larry’s very interesting and provocative (in a good way) paper on ‘how recent developments in statistical modeling and inference have [a] changed the intended scope of [...]
I always wondered what went on there. $380 x 500 people, that’s $190,000! I’ll have to remember to ask for more money next time I’m asked to speak for a commercial organization.
Editor’s Note: This is the counterpoint in our series of posts on the value of abstraction in graduate education. See Brian’s defense of abstraction on Monday and the comments on his post, as well as the comments on our original teaser post for mor...
Somebody asked me to speak sometime at a data visualization meetup. I think I spoke there a year or two ago but I could do it again. Last time I spoke on Infovis vs Statistical Graphics, this time I could just go thru the choices involved in a few zillion graphs I’ve published over the [...]
Howard Wainer points me to a thoughtful discussion by Moti Nissani on “Psychological, Historical, and Ethical Reflections on the Mendelian Paradox.” The paradox, as Nissani defines it, is that Mendel’s data seem in many cases too good to be true, yet Mendel had a reputation for probity and it seems doubtful that he had a [...]
John Cook's discussion at Wrong and unnecessary — The Endeavour and the comments to that post are all worth reading (I rarely say that about comments to a post). The post is ostensibly on whether a linear model is useful even though it is no, in the ...
Meter Objects [meterobjects.org], developed by Patrick Kochlik and Monika Hoinkis, questions the nature of the whole self-monitoring (also known as the 'quantified self') movement. The carefully designed collection of objects aims to embrace the act o...
Ole Rogeberg writes: After reading your recent post, I thought you might find this interesting – especially the scanned interview that is included at the bottom of the posting. It’s an old OMNI interview with Walter Stewart that was the first thing I read (at a young and impressionable age ;) about the prevalence of [...]
I was asked by a reader how I created Figure 7.2 of the book, reproduced at right, which shows the progression of discrete position probabilities at each step in a simple Metropolis algorithm. I couldn't find the original program, so I made a new one, ...
