Blog Archives

Student-Run Conference in Data Science

May 5, 2016
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Student-Run Conference in Data Science

I’d like to urge all of you in Northern California to attend iidata, a student-run conference in data science, to be held on the UC Davis campus on May 21. According to the Web page, iidata is a one-day, collegiate-level Data Science convention aimed at educating students in the new, thrilling field of data science. … Continue reading...

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Talk on regtools and P-Values

April 28, 2016
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Talk on regtools and P-Values

I’m deeply greatful to Hui Lin and the inimitable Yihui Xie for arranging for me to give a “virtual seminar talk” to the Central Iowa R Users Group. You can view my talk, including an interesting Q&A session, online. (The actual start is at 0:34.) There are two separate topics, my regtools package (related to … Continue reading...

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GTC 2016

March 29, 2016
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GTC 2016

I will be an invited speaker at GTC 2016, a large conference on GPU computation. The main topic will be usage of GPU in conjunction with R, and I will also speak on my Software Alchemy method, especially in relation to GPU computing.. GTC asked me to notify my “network” about the event, and this … Continue reading...

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Even Businessweek Is Talking about P-Values

March 28, 2016
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Even Businessweek Is Talking about P-Values

The March 28 issue of Bloomberg Businessweek has a rather good summary of the problems of p-values, even recommending the use of confidence intervals and — wonder of wonders — “ at the evidence as a whole.” What, statistics can’t make our decisions for us?  :-) It does make some vague and sometimes puzzling statements, … Continue reading...

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P-values: the Continuing Saga

March 10, 2016
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P-values: the Continuing Saga

I highly recommend the blog post by Yoav Benjamini and Tal Galili in defense of (carefully used) p-values. I disagree with much of it, but the exposition is very clear, and there is a nice guide to relevant R tools, including for simultaneous inference, a field in which Yoav is one of the most prominent, … Continue reading...

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Further Comments on the ASA Manifesto

March 9, 2016
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Further Comments on the ASA Manifesto

On Tuesday I commented here on the ASA (in their words) “Position on p-values:  context, process, and purpose.” A number of readers replied, some of them positive, some mistakenly thinking I don’t think statistical inferences are needed, and some claiming I overinterpreted the ASA’s statement. I’ll respond in the current post, and will devote most … Continue reading...

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After 150 Years, the ASA Says No to p-values

March 7, 2016
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After 150 Years, the ASA Says No to p-values

Sadly, the concept of p-values and significance testing forms the very core of statistics. A number of us have been pointing out for decades that p-values are at best underinformative and often misleading. Almost all statisticians agree on this, yet they all continue to use it and, worse, teach it. I recall a few years … Continue reading...

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Quick Intro to NMF (the Method and the R Package)

March 6, 2016
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Quick Intro to NMF (the Method and the R Package)

Nonnegative matrix factorization (NMF) is a popular tool in many applications, such as image and text recognition. If you’ve ever wanted to learn a little bit about NMF, you can do so right here, in this blog post, which will summarize the (slightly) longer presentation here. The R package NMF will be used as illustration. … Continue reading...

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Innumeracy, Statistics and R

March 1, 2016
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Innumeracy, Statistics and R

A couple of years ago, when an NPR journalist was interviewing me, the conversation turned to quantitative matters. The reporter said, only half jokingly, “We journalists are innumerate and proud.” :-) Some times it shows, badly. This morning a radio reporter stated, “Hillary Clinton beat Bernie Sanders among South Carolina African-Americans by an almost 9-to-1 … Continue reading...

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50% Draft of Forthcoming Book Available

March 1, 2016
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50% Draft of Forthcoming Book Available

As I’ve mentioned here a couple of times, I am in the midst of writing a book, From Linear Models to Machine Learning: Regression and Classification, with Examples in R. As has been my practice with past books, I have now placed a 50% rough draft of the book on the Web. You will see … Continue reading...

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