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Comment by EpiMath | Hacker News Reader

Interesting, thanks. ( Like your username too, despite him being slightly denigrated in the linked article. ) I personally think that it is good to have a basic grounding in some kind of fundamental "real" programming language before you get into s-plus ( R ) or any other more domain-specific language. The main reason being that you will better understand the compromises, limitations and shortcomings. I like R but as a programmer I've seen some awful code written in it!

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Yes, if you read further on the blog, you'll see I'm more than slightly denigrating. I read a book recently called The Cult of Statistical Significance and it's really turned me against Fisher. Not only do I see his methods as sub-standard to Bayesian analysis, he was really mean and disparaging himself to those folks. It's interesting, my username is what it is because he used to be my hero! Just 6 months ago, I really considered him to be the father of modern science. Now I basically see his work as mostly enabling mediocre scientists to rise through the ranks. This is what I mean by that: http://www.economist.com/blogs/graphicdetail/2013/10/daily-c...

I've spent my career thinking about these same issues. And certainly Fisher was, well, abrasive to put it mildly. I've read much of his early work and I think the intended context has mostly been lost. Many modern statisticians ( of the "frequentist" persuasion ) use a strange and awkward combination of fisherian and neyman-pearson. We talk about "p-values" but then interpret them as hypothesis tests with long-term error probabilities ( Fisher disavowed this interpretation of p-values, and insisted they did not have a long run probabilistic interpretation but were a measure only of evidence against the null in the particular experiment. ) I think Fisher gets a bad rap for a lot of later bastardization of his work. ( I'm sure it did not help that he was not a likable person, or his valid but misguided and testimony about tobacco. )

Still, I'm sympathetic to your position and can understand how you'd come to that way of thinking. I'm not convinced even a diehard Bayesian would completely disagree with Fisher's more restricted and stringent interpretation of p-values. Or at least they would see it as a big step up from the more common usage you are referencing.

When did ideas get muddied by personality? I see this in the whole Ender's Game debate and in this Fisher debate. We need to compare ideas outside of the personality THAN we can separate the idea for the person.

In our history (Historical Philosophy/Theology Major) you would be apsolutely shocked at the lives of great thinkers and disapprove so much of their lives but MOST people don't know. This is the issue with open lives we know so much more about people. It is never just a book or an idea we can learn maybe to much???

What a silly thing to think. I think you'll find that Fisher's development of likelihood and explicit probabilistic modeling is rather important in Bayesian statistics. You'll also find that Fisher was not only one of the top 3 if not the 20th century's most important theoretical statistician, but that he was one of the top 3 if not the 20th century's most important theoretical geneticist. This sort of fanboy Bayesianism is really rather embarrassing.

Yes, I really do value and see the genius in likelihood, but Fisher is idolized in a really unhealthy way in statistics IMO. I'm a Bayesian fanboy because it works. I spent > 1 yr. trying to get Fisher's testing framework to yield business success. Positive results came, but were always a slog and more often than not it's use failed. As soon as I switched to Bayesian methods, consistent success started happening. It's exciting.

I don't think saying R is not a "real" is a fair characterisation. It is not a domain-specific language in the sense the term is commonly used (SQL and ggplot2 are domain specific languages, R is not). R is a real programming language with inspirations from Scheme and Common Lisp; just because there's a lot of bad R code doesn't mean that the language isn't bad.

If you are responding to my comment, I agree with you. I like the R language very much and use it. I may not have said what I meant well enough. What I mean is that there is a tendency with R programmers and much more so with SAS or Stata not to think about the guts of the program and what is really happening. The data frame in R is a nice framework for thinking and programming, but it does not promote thinking about whether i/o is to disk or memory, or whether iterations or loops or recursion is efficient, or overall program efficiency, reuse etc. Programmers tend to rely on the underlying system to worry about memory allocation disk i/o etc. There are many problems where these details matter. So much time is spent on the statistical problem and what procedure or function to call, rather than the algorithm at a deeper level. These details can be handled, but are not so "front and center". Matlab and others similarly. I have seen enterprise-class servers brought to their knees by a poorly written R program... ( you can say lots of things about how that should not be possible, or how that can happen with other languages, and I'd agree, but I still think it is more likely in a context that does not encourage programmers to think "closer to the metal" about where data is and what is happening to it. )

I've seen some great R code too... so this is a complicated topic and has to do with who is writing the code as much as R itself.

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