pav3l

Just curious, was your site hosted at the same place?

>And let know that the possible options before the Zionist soldier entered Gaza are four options, no more! 1- Either will be killed 2- or will be captivated 3- or will be handicapped 4- or will be mentally ill

>We Muslims are people who love to drink bloods. And we learn that the taste of your blood is delicious !!

Who are these morons?

EDIT: The title should be changed. some Pakistani kids seem to claim responsibility, not Palestinians. Also "Pro"? Really?

How do people use these sort of things? I'm genuinely curious. It's not even that fancy of a calc app, since you can't support numpy or plotting.

If someone could implement something similar to http://www.mathworks.com/mobile/ for Python, now that would be cool!

This is an excellent essay. I am coming from a math background and mostly picked up programming on my own. Even though I may not directly use algebra or analysis in my programming, usually what I see as elegant and neat from a mathematical perspective later turns out to be more efficient and readable from practical point of view.

>1) These script kiddies are not Anonymous;

I think you may be overestimating "the real Anonymous".

> I'm reading lots of articles lately that misuse statistics, and I don't think this post puts your company in a good light.

Actually I didn't even see any inferential statistics in the post. He just reported observed values and drew his conclusions. At least running something like a chi-squared test could give me an idea of how unlikely it would be to observe those different proportions among the different groups just by pure chance.

I just ordered it 2 days ago directly from O'Reilly website (they currently have "buy 2 get 1 free" promotion, just use code OPC10, http://shop.oreilly.com/product/0636920025108.do). Really excited to read it when it comes. In case you're curious the other 2 books I ordered were "Python for Data Analysis" and "JavaScript Web Applications" which also look very promising.

Edit: Sorry, not a referral link.

I had know idea this has been an issue anyone cared about. Is there some back story that would explain this petition?

>High-end software development skills will become even more scarce.

It's not obvious to me. Can you explain your reasoning?

This reminds me of the mug-shot removal service I read about while ago http://www.wired.com/threatlevel/2011/08/mugshots/

For python people, I found this 30 min talk by Ned Batchelder extremely helpful: https://www.youtube.com/watch?v=sgHbC6udIqc

Yes, I originally started http://news.ycombinator.com/item?id=4769667 with title "Andrew Gelman: I don't like this cartoon", but for some reason mods decided to get rid of "Andrew Gelman" in the title. I mean, the whole point is that it's a very famous statistician, not just another blogger ranting.

Thanks so much! Just tried it and the setup binaries worked like a charm! 20 seconds for the whole experience including downloading and testing. Very different from how I remember my experience with lxml on Windows when I tried it before! They should definitely have a link to this website from http://lxml.de/installation.html#ms-windows

>lxml is awesome, but difficult to install

So true... I often need to write something that will run on a Windows machine and I just end up having to use the old version of Beautiful Soup (before it became dependent on lxml). Pretty frustrating.

When you are reporting, say, a p-value from your ANOVA F-test, you are making formal mathematical assumptions, such as normal marginal distribution of your dependent variable. A lot of Frequentist methods (hypothesis testing) are really just mathematical shortcuts from times when computation was more expensive. The problem is, many people tend to misuse the tests where they are not appropriate either because those give "better" answers, or simply out of ignorance.

>Surely, only one is true.

This is my general comment about statistics and data analysis without going into the specifics of Freq vs Bayes:

As anyone who ever worked with real-world data can tell you, for the most part data analysis is more of an art than exact science. Sure, it's math, and once you pick the right model, there is (usually) one correct way to solve it. The problem is that most mathematical methods come with assumptions that are almost never met in practice, so you have to make a lot of (often fairly arbitrary) decisions about how to go about your data analysis. How do you handle missing data cases? Is your data normally distributed enough to justify the use of some method? Is the sample large enough? Are those residuals in your model diagnostics random enough? Does that trend line look linear enough? What prior information can I use (and how?) to formally add value to the model? Real world is messy.

I really like this sentence:

> All statisticians use prior information in their statistical analysis. Non-Bayesians express their prior information not through a probability distribution on parameters but rather through their choice of methods.

Also, from the comments:

>My problem is ultimately not with the cartoon. My problem is that there are practitioners and teachers of statistics who spread cartoonish ideas about statistical methods without recognizing these ideas are inaccurate.

Very cool, but unfortunately things "the web can do" are limited by things "bad popular web-browsers can do"

Relevant blog post by the author: http://mflux.tumblr.com/post/29879318929/generativemachines

Yes, set up a private tunnel, don't rely on Tor, Google blocks a lot of their exit nodes, so it's just unusable most of the time.

Another discussion: http://news.ycombinator.com/item?id=4764376

I'm assuming this is a follow-up on http://news.ycombinator.com/item?id=4752047

Wow, that is crazy!! Even though i have 2 math degrees and am doing applied math and stats for a living, there is a very good chance I'd fail such an exam if I took it now!

Just curious, are there people here who went through or are going through the MIT Tech Entrepreneurship program? Or maybe just took some courses from them? What are your thoughts?

Google is an excellent search engine. If you have privacy concerns, don't store your personal information with Google. It's really that simple. Switching to other search engines because of privacy concerns is just silly in my opinion. I have those concerns as well, but instead of missing out on Google search I choose to not use any of Google's other services (e.g. Gmail, G+, etc.) that would store my personal information (and possibly tie it to my searches). If you want to take advantage of webmaster tools, analystics, etc. just create an account just for that, and don't use it for actual communication.

>If someone wants to communicate with me, they do the same. I get texts all the time that start similar to "hey, facebook-challenged friend, theres X going on next weekend, come hang" or a phonecall/email saying the same, which leads into actual personal communication.

So, the change is 1000% positive because people now contact you personally about facebook events? I don't really get it.

Facebook is a tool, and it can definitely be helpful as long as you're in control. I only use it as an extension of my email (because of facebook some of my friends only check their personal email once every few days). I never post things, like things, or comment on things. If I were to delete my account now, I would simply lose a lot of contacts that I don't want to lose.

So, can someone please explain me why "Closing off the department’s computers to the Internet is a complicated matter"? I mean is it so hard to have sensitive databases on an internal network, that is disconnected from the outside world and only has a limited white list of media devices that can be connected to it?

How are those two easily distinguishable, when the major selling point of your skill set is that you worked on and designed a system whose workings are the confidential information.

Facebook specifically prohibits this. If I'm not mistaken only the account holder can download the data, you need to enter your password and bypass captcha. Also the download link is sent to your email.

+1 for Tom Mitchell's book. Although it may appear a little outdated, it is an excellent introduction to ML. Highly recommend doing the exercises (in whatever language you'll be working, not necessarily in C), especially the Neural Nets face recognition one. The book doesn't cover SVM, so you might want to learn about those elsewhere. Also if you don't have a good background in basic applied stats (linear models, logistic regression, etc), I suggest you brush up on that as well.

It would be interesting to do some sentiment analysis on comments and look at the statistics of dissmissive/approving top comments and all comments in general in HN threads.