Leonard A. Stefanski

                                       

R. A. Fisher Distinguished Professor
Department of Statistics,
North Carolina State University,
Raleigh, NC, 27695-8203.

len_stefanski@ncsu.edu
Tel: (919) 515-1945
Fax: (919) 515-1169

Education:     Current Research Interests:
  • Variable selection.
  • Measurement error models.
  • Generalized linear models.
  • Environmental statistics.
  • Trout distributions.
   

215 Influential Developments in Statistics Deconvolution made the list!

Measurement Error Models and Happiness SIMEX Increases Coefficient of Happiness!

Residual Plots   as described in   The American Statistician : Residual (Sur)Realism

Believe it or Not! You are looking at plots of residuals versus predicted values from the fit of multiple linear regression models to two different data sets. Curious? Click on an image and see how it's done (alas, these are not naturally occurring 1-in-a-trillion-trillion-trillion chance random scatter plots).

Homer Simpson. Mathematics is no stranger to the Simpsons, see simpsonsmath.com, but this may be the first time that Homer has dabbled in statistics. It appears that he has embedded himself into an infinite do loop! The image above is a spoof of a scene from a Simpson's episode in which Homer tackles a difficult mathematical derivation. Click on the image to learn how it was constructed.

Ronald Aylmer Fisher (1890-1962). This is an embedded-image version of a well-known image of Fisher operating a calculating machine. You can find the original at several places on the web, see here for example. Click on the image to learn how it was constructed.

Below is an animated illustration of a nifty feature available in the new version of JMP software---interactive tuning parameter selection for variable selection methods. The top-right panel contains the forward-selection, BIC criterion selection curve for a data set with the Homer Simpson image embedded in the residual plot (n = 8406, p = 99, 4 nonzero). As the tuning parameter moves right to left toward the minimum of BIC curve, the corresponding parameter estimates can be tracked on the coefficent path plots (top-left panel); and the resulting residual plots appear in the lower-left panel. Thanks to JMP developer and die-hard Wolfpack fan, Clay Barker, for preparing the animation. Read more about Clay's JMP interactive model building routines.

Projections can be revealing or misleading. The shadow art below by Shigeo Fukuda is made of 848 welded knives, spoons, and forks (the kind you eat with, not the front forks of a motorcycle). It is titled Lunch with a Helmet On. See more examples of shadow art. Thanks to Munir Winkel for bringing this to my attention.

Another article of interest from The American Statistician: The North Carolina Lottery Coincidence ...

... and my favorite citations of it:

North Carolina lottery repeat numbers: (in a lovely introspective journal article written in the first person) Leonard A. Stefanski. "The North Carolina Lottery Coincidence," The American Statistician, 62.2 (2008): 130-134 from Evil by Design: Interaction Design to Lead Us into Temptation by Chris Nodder.

A humorous story on a similar event in the North Carolina Lottery can be found in L. A. Stefanski, "The North Carolina Lottery Coincidence," The American Statistician, 62 (2008): 130-134 from Understanding Probability by Henk Tijms.

If you've stuck with me this far, you're probably really interested in the subject matter! I would recommend the following article to gain additional perspective: Stefanski, Leonard A. (2008). The North Carolina lottery coincidence. The American Statistician. 62, 130-134. Stefanski reflects upon the different interests of statisticians and laypersons (including the media) in understanding rare occurrences involving lotteries, sports, and perhaps other phenomena. Whereas laypersons seem to be interested in what Stefanski calls a "narrow" perspective (e.g., Aaron Hill's achievement), statisticians embrace a "wide" perspective, seeking to contextualize an occurrence in the larger set of opportunities for an event to occur. Writes Stefanski: Statisticians should point out when seemingly rare events are not really that rare. But in doing so we should not lose sight of the fact that for some human interest stories, a probability calculation from the "narrow perspective" is appropriate. My hunch is that we sometimes do lose sight of the human-interest angle because we are geared toward the "wide" perspective (p. 131). from The Hot Hand in Sports by Alan Reifman.
Some heavier reading ...

                                    The shadowy images you see around in the background are large trout holding in about six feet of water.

If these books don't satisfy your curiosity about my research, read some of my papers.

R Programs for Visualizing the NRC Rankings Data NRC Rankings Data.

From the WABAC Machine ... Track and Field, May 13, 1971 or Basketball, Feb 9, 1970

Don't know what the WABAC Machine is?

My Curriculum Vitae


The material on this web page is based upon work supported by the National Science Foundation under Grant No. 0504283. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation.

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