The bottom line of this post is for you to go to:
Stack Exchange Q&A site proposal: Statistical Analysis
And commit yourself to using the website for asking and answering questions.

(And also consider giving the contender, MetaOptimize a visit)

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Statistical analysis Q&A website is about to go into BETA

A month ago I invited readers of this blog to commit to using a new Q&A website for Data-Analysis (based on StackOverFlow engine), once it will open (the site was originally proposed by Rob Hyndman).
And now, a month later, I am happy to write that over 500 people have shown interest in the website, and choose to commit themselves. This means we we have reached 100% completion of the website proposal process, and in the next few days we will move to the next step.

The next step is that the website will go into closed BETA for about a week. If you want to be part of this – now is the time to join (<--- call for action people).
From being part in some other closed BETA of similar projects, I can attest that the enthusiasm of the people trying to answer questions in the BETA is very impressive, so I strongly recommend the experience.

If you won't make it by the time you see this post, then no worries - about a week or so after the website will go online, it will be open to the wide public.

(p.s: thanks Romunov for pointing out to me that the BETA is about to open)

p.s: MetaOptimize

I would like to finish this post with mentioning MetaOptimize. This is a Q&A website which is of a more “machine learning” then a “statistical” community. It also started out some short while ago, and already it has around 700 users who have submitted ~160 questions with ~520 answers given. From my experience on the site so far, I have enjoyed the high quality of the questions and answers.
When I first came by the website, I feared that supporting this website will split the R community of users between this website and the area 51 StackExchange website.
But after a lengthy discussion (published recently as a post) with MetaOptimize founder, Joseph Turian, I came to have a more optimistic view of the competition of the two websites. Where at first I was afraid, I am now hopeful that each of the two website will manage to draw a tiny bit of different communities of people (that would otherwise wouldn’t be present in the other website) – thus offering all of us a wider variety of knowledge to tap into.

See you there…

A new statistical analysis Q&A website launched

While the proposal for a statistical analysis Q&A website on area51 (stackexchange) is taking it’s time, and the website is still collecting people who will commit to it,
Joseph Turian, who seems a nice guy from his various comments online, seem to feel this website is not what the community needs and that we shouldn’t hold up on our questions for the website to go online. Therefore, Joseph is pushing with all his might his newest creation “MetaOptimize QA“, a StackOverFlow like website for (long list follows): machine learning, natural language processing, artificial intelligence, text analysis, information retrieval, search, data mining, statistical modeling, and data visualization.
With all the bells and whistles that the OSQA framework (an open source stackoverflow clone, and more, system) can offer (you know, rankings, badges and so on).

Is this new website better then the area51 website? Will all the people go to just one of the two websites. or will we end up with two places that attracts more people then we had to begin with? These are the questions that come to mind when faced with the story in front of us.

My own suggestion is to try both websites (the stackoverflow statistical analysis website to come and “MetaOptimize QA“) and let time tell.

More info on this story bellow.

MetaOptimize online impact so far

The need for such a Q&A site is clearly evident. With just several days after being promoted online, MetaOptimize has claimed the eyes of almost 300 users, submitting 59 questions and 129 answers.
Already many bloggers in the statistical community have contributed their voices with encouraging posts, here is just a collection of the post I was able to find with some googling:

• http://hunch.net/?p=1425
• http://ebiquity.umbc.edu/blogger/2010/06/30/training-examples-qa-stackoverflow-for-nlp-and-ml/
• http://lingpipe-blog.com/2010/06/29/training-examples-a-stack-overflow-for-nlp-and-ml-and/
• http://www.stat.columbia.edu/~cook/movabletype/archives/2010/06/question_answer.html
• http://kaggle.com/blog/2010/07/02/new-machine-learning-and-natural-language-processing-qa-site/
• http://www.jroller.com/otis/entry/metaoptimize_com_q_a_site
• http://sbseminar.wordpress.com/2010/06/17/statistics-version-of-mathoverflow-looking-for-beta-testers/
• http://myumbc3.my.umbc.edu/news/1841
• http://ebiquity.umbc.edu/blogger/2010/06/30/training-examples-qa-stackoverflow-for-nlp-and-ml/

But is it goos to have two websites?

But wait, didn’t we just start pushing forward another statistical Q&A website two weeks ago?  I am talking about the Stack Exchange Q&A site proposal: Statistical Analysis.

So what should we (the community of statistical minded people) to do the next time we have a question?

Should we wait for Stack Exchange offer for a new website to start?  Or should we start using MetaOptimize?

Update: after lengthy e-mail exchange with Joseph (the person who founded MetaOptimize), I decided to erase what I originally wrote as my doubts, and instead give a Q&A session that him and I have had in the e-mails exchange.  It is a bit edited from what was originally, and some of the content will probably get updated – so if you are into this subject, check in again in a few hours

Honestly, I am split in two (and Joseph, I do hope you’ll take this in a positive way, since personally I feel confident you are a good guy).  I very strongly believe in the need and value of such a Q&A website.  Yet I am wondering how I feel about such a website being hosted as MetaOptimize and outside the hands of the stackoverflow guys.
On the one hand, open source lovers (like myself) tend to like decentralization and reliance on OSS (open source software) solutions (such as the one OSQA framework offers).  On the other hand, I do believe that the stackoverflow people  have (much) more experience in handling such websites then Joseph.  I can very easily trust them to do regular database backups, share the websites database dumps with the general community, smoothly test and upgrade to provide new features, and generally speaking perform in a more  experienced way with the online Q&A community.
It doesn’t mean that Joseph won’t do a great job, personally I hope he will.

Q&A session with Joseph Turian (MetaOptimize founder)

Tal: Let’s start with the easy question, should I worry about technical issues in the website (like, for example, backups)?

Joseph:

They provide email and chat support for OSQA users.

I will commit to putting up regular automatic database dumps, whenever the OSQA team implements it:
http://meta.osqa.net/questions/3120/how-do-i-offer-database-dumps
If, in six months, they don’t have this feature as part of their core, and someone (e.g. you) emails me reminding me that they want a dump, I will manually do a database dump and strip the user table.

Also, I’ve got a scheduled daily database dump that is mirrored to Amazon S3.

Tal: Why did you start MetaOptimize instead of supporting the area51 proposal?
Joseph:

1. On Area51, people asked to have AI merged with ML, and ML merged with statistical analysis, but their requests seemed to be ignored. This seemed like a huge disservice to these communities.
2. Area 51 didn’t have academics in ML + NLP. I know from experience it’s hard to get them to buy in to new technology. So why would I risk my reputation getting them to sign up for Area 51, when I know that I will get a 1% conversion? They aren’t early adopters interested in the process, many are late adopters who won’t sign up for something until they have too.
3. If the Area 51 sites had a strong newbie bent, which is what it seemed like the direction was going, then the academic experts definitely wouldn’t waste their time. It would become a support
   community for newbies, without core expert discussion. So basically, I know that I and a lot of my colleagues wanted the site I built. And I felt like area 51 was shaping the communities really incorrectly in several respects, and was also taking a while.  I could have fought an institutional process and maybe gotten half the results above and it took a few months, or I could just build the site and invite my friends, and shape the community correctly.

Besides that, there are also personal motives:

• I wanted the recognition for having a good vision for the community, and driving forward something they really like.
• I wanted to experiment with some NLP and ML extensions for the Q+A software, to help organize the information better. Not possible on a closed platform.

Tal: Me (and maybe some other people) fear that this might fork the people in the field to two websites, instead of bringing them together. What are your thoughts about that?
Joseph:
How am I forking the community? I’m bringing a bunch of people in who wouldn’t have even been part of the Area 51 community.
Area 51 was going to fork it into five communities: stat analysis, ML, NLP, AI, and data mining. And then a lot fewer people would have been involved.

Tal: What are the things that people who support your website are saying?
Joseph:
Here are some quotes about my site:

Philip Resnick (UMD): “Looking at the questions being asked, the people responding, and the quality of the discussion, I can already see this becoming the go-to place for those ‘under the hood’ details
you rarely see in the textbooks or conference papers. This site is going to save a lot of people an awful lot of time and frustration.”

Aria Haghighi (Berkeley): “Both NLP and ML have a lot of folk wisdom about what works and what doesn’t. A site like this is crucial for facilitating the sharing and validation of this collective knowledge.”

Alexandre Passos (Unicamp): “Really thank you for that. As a machine learning phd student from somewhere far from most good research centers (I’m in brazil, and how many brazillian ML papers have you
seen in NIPS/ICML recently?), I struggle a lot with this folk wisdom. Most professors around here haven’t really interacted enough with the international ML community to be up to date”
(http://news.ycombinator.com/item?id=1476247)

Ryan McDonald (Google): “A tool like this will help disseminate and archive the tricks and best practices that are common in NLP/ML, but are rarely written about at length in papers.”

esoom on Reddit: “This is awesome. I’m really impressed by the quality of some of the answers, too. Within five minutes of skimming the site, I learned a neat trick that isn’t widely discussed in the literature.”
(http://www.reddit.com/r/MachineLearning/comments/ckw5k/stackoverflow_for_machine_learning_and_natural/c0tb3gc)

Tal: In order to be fair to area51 work, they have gotten wonderful responses for the “statistical analysis” proposal as well (see it here)
I have also contacted area51 directly and asked them and invited them to come and join the discussion. I’ll update this post with their reply.

So what’s next?

I don’t know.
If the Stack Exchange website where to launch today, I would probably focus on using it and hint to the site for MetaOptimize (for the reasons I just mentioned, and also for some that Rob Hyndman maintained when he first wrote on the subject).
If the stack exchange version of the website where to start in a few weeks, I would probably sit on the fence and see if people are using it.  I suspect that by that time, there wouldn’t be many people left to populate it (but I could always be wrong).
And what if the website where to start in a week, what then?  I have no clue.
Good question.
My current feeling is that I am glad to let this play out.
It seems this is a good case study for some healthy competition between platforms and models (OSQA vs stackoverflow/area51-system) – one that I hope will generate more good features from both companies. And also will make both parties work hard to get people to participate.
It also seems that this situation is getting many people in our field to be approached with the same idea (Q&A website). After Joseph input on the subject, I am starting to think that maybe at the end of the day this will benefit all of us. Instead of forking one community into two, maybe what we’ll end up with is getting more (experienced) people online (into two locations) that would otherwise would have stayed in the shadows.

The verdict is still out, but I am a bit more optimistic than I was when first writing this post. I’ll update this post after getting more input from people.

And as always – I would love to know your thoughts on the subject.

This post will eventually grow to hold a wide list of books on statistics (e-books, pdf books and so on) that are available for free download.  But for now we’ll start off with just one several books:

• The Elements of Statistical Learning written by Trevor Hastie, Robert Tibshirani and Jerome Friedman. you can legally download a copy of the book in pdf format from the authors website! Direct download (First discovered on the “one R tip a day” blog)
• Statistics (Probability and Data Analysis) – a wikibook. Download link
• Introduction to Statistical Thought by Michael Lavine.  The book is organized into seven chapters: “Probability,” “Modes of Inference,” “Regression,” “More Probability,” “Special Distributions,” “More Models,” and “Mathematical Statistics.” and makes extensive use of R.  Here is a favoring review the book received in JASA. 328 pages. Download link (approx. 40 mbyte)
• Street-Fighting Mathematics by Sanjoy Mahajan. Download link
• Statistical Analysis with the General Linear Model by Miller and Haden. an introductory textbook describing statistical analysis with analysis of variance (ANOVA, including repeated-measures and mixed designs), simple and multiple regression, and analysis of covariance. 274 pages. Download link (p.s: this book makes no reference to R.  see here for R tutorials and functions for performing repeated measures anova)
• Collaborative Statistics by Barbara Illowsky and Susan Dean.  This textbook is intended for introductory statistics courses.  627 pages.  R is not used in this book.  Download link
• Using R for Introductory Statistics by John Verzani Publisher: Chapman & Hall/CRC 2004 ISBN/ASIN: 1584884509 ISBN-13: 9781584884507 Number of pages: 114 Description: The author presents a self-contained treatment of statistical topics and the intricacies of the R software. The book treats exploratory data analysis with more attention than is typical, includes a chapter on simulation, and provides a unified approach to linear models. This text lays the foundation for further study and development in statistics using R. Download link
• R Graphics (Three chapters only) by Paul Murrell ISBN: 9781584884866 ISBN 10: 158488486X Publication Date: July 29, 2005 Number of Pages: 328 Description: Chapter 1: An Introduction to R Graphics Chapter 4: Trellis Graphics: The Lattice Package Chapter 5: The Grid Graphics Model Download link (see scripts and images here)
• Using R Download link
• R intro Download link
• Psychometric Theory with Applications in R by William Revelle (a work in progress) Download link
• A great long list of R related texts, for free download, can be found here.
• Using Graphs Instead of Tables website link (This web page accompanies the article “Using Graphs Instead of Tables in Political Science”, by Jonathan Kastellec and Eduardo Leoni, which appears in the December 2007 issue of Perspectives on Politics. It contains complete replication code for all the graphs that appear in the text)
• IPSUR: Introduction to Probability and Statistics Using R by G. Jay Kerns, is FREE (in the GNU sense of the word) and comes with a plugin for Rcmdr. 412 pages. Download link (first discovered through the Revolution blog)
• Multivariate Statistics with R by Paul J. Hewson. 189 pages. Download link (first discovered through open text book blog)
• R Programming – a wikibook. (no PDF version is available as of yet)
• Introduction to Statistical Thinking (With R, Without Calculus) – By Benjamin Yakir
• A History of Parametric Statistical Inference from Bernoulli to Fisher, 1713 to 1935 – By Anders Hald
• Principles of Uncertainty (direct link to pdf), by Jay Kadane (got a great review by xian)

Several of these books were discovered through a CrossValidated discussion.

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Know of any more e-books freely available for download? Please write to me about them in the comments.