For the past few weeks Time Out New York‘s Dating columnist, Jamie Bufalino, has been fielding letters discussing the ratio of homosexual to heterosexual questions he answers.  The readers suggested that disproportionate attention is paid to Gay and Lesbian issues compared to the Gay and Lesbian proportion of the general population.      

Jamie rudely called his readers “ass-wipes” and repeatedly told them to “remove your head from your ass.”  He also professed to have “no idea what the percentage is of gay/bi versus straight issues that end up in the column.”  

One question and response:  

Q I see statistics that show NYC to be 6 percent gay, lesbian and bi, and yet in “Get Naked” you feature letters from them almost to the exclusion of heteros. Why the preoccupation with them in your column? It doesn’t seem right or logical. As one of the other 94 percent, I am disappointed and offended weekly.   

A All I can say is: You’ve got your head up your butt. Just in the past month or so, I’ve answered letters from a straight guy with a weird fetish that suddenly stopped delivering the jollies it used to, a straight guy who was juggling a woman from the Ukraine and a woman from Jersey, a woman who had an issue with sticking her finger up her boyfriend’s butt, a 19-year-old woman who was getting pressured to have sex with her boyfriend, and on and on. If, for some reason, you happen to be obsessing over the gay and bi questions and not acknowledging the straight ones, that’s your issue, not mine.  

And another:  

Q I always read your column to see if I can learn something and just for shits and giggles. The one thing that has always bothered me is your preoccupation with gay and bi problems. Gays and lesbians get their own special section of three to four pages!  

A First of all, dude, you sound like one of those total ass-wipes who believes that gay people somehow have all these special privileges that straight people aren’t entitled to. Honestly, I have no idea what the percentage is of gay/bi versus straight issues that end up in the column, because it doesn’t matter. If you removed your head from your ass, you’d realize that so many sexual issues are universal and that you can learn something from all sorts of people who don’t fit into your specific demographic.  

When confronted with the data he once again reffered to a “head lodged up [a] rectum” and suggested the reader was “paranoid.”  

Q As a statistician I am disappointed by your response to a question in the November 4 issue [TONY 788]. The reader wrote, “I see statistics that show NYC to be 6 percent gay, lesbian and bi, and yet in ‘Get Naked’ you feature letters from them almost to the exclusion of heteros. Why the preoccupation with them in your column? … As one of the other 94 percent, I am disappointed and offended weekly.” You responded by citing individual examples of heterosexual questions you’ve fielded, which is not a valid form of proof. I went through about ten months’ worth of “Get Naked” columns on the TONY website and found that approximately 19 percent of the questions were from gay (15 percent) or lesbian (4 percent) readers. Whether or not that percentage is representative of the general population is not my concern. I just feel that Jamie should have his data correct and not write, “You’ve got your head up your butt.”  

A I seriously cannot believe I am still getting letters about this. Okay, Mr. Disappointed Statistician: If you don’t want to come off as someone who has his head lodged up his rectum, it would be an awesome idea not to leap to the defense of some jackass who claims I cater to homo letters “almost to the exclusion of heteros” and then point out that straight issues actually make up a full 81 percent of the subject matter here in “Get Naked.” What I want to know is, why are you even keeping score? Are you really that insecure about the amount of attention heterosexual sex gets in the media? If so, that’s both laughable and sad. This is the last time I’m addressing this, so here’s my final bit of advice to you (and your like-minded brethren): Stop being so paranoid.  

Since Jamie is so rude to his readers and clearly doesn’t have any sense of the data, I thought I’d take a look at the numbers.  Results after the break.   

Continue reading

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Jared Lander is the Chief Data Scientist of Lander Analytics a New York data science firm, Adjunct Professor at Columbia University, Organizer of the New York Open Statistical Programming meetup and the New York and Washington DC R Conferences and author of R for Everyone.

Data Mafia Shirt

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Jared Lander is the Chief Data Scientist of Lander Analytics a New York data science firm, Adjunct Professor at Columbia University, Organizer of the New York Open Statistical Programming meetup and the New York and Washington DC R Conferences and author of R for Everyone.

The Father of Gerrymandering
The Father of Gerrymandering

The Wall Street Journal is reporting that even with all the concern around gerrymandering that in reality the upcoming redistricting probably won’t have much affect on upcoming elections.  Gary King is mentioned as having written a paper “that helped demonstrate the relative impotence of partisan redistricting” yet “he favors the efforts to create a statistical method that would replace it.”  I personally am always for using math and hard numbers to solve any problem whenever possible.

The article also mentioned a “conference last year in Washington, D.C., researchers proposed alternatives.”  David Epstein presented a paper at that conference that Andy Gelman and I worked on.

While the article quoted one of Dr. Gelman’s papers it unfortunately did not mention him, or any of us by name.  However, the accompanying blog post did mention both Dr.s Gelman and Epstein with specific quotes of them and their work.

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Jared Lander is the Chief Data Scientist of Lander Analytics a New York data science firm, Adjunct Professor at Columbia University, Organizer of the New York Open Statistical Programming meetup and the New York and Washington DC R Conferences and author of R for Everyone.

Today is World Statistics Day as declared by the United Nations.  There are events all over the world including a mourning for the Canadian census.  The official US event (pdf) is in Washington, DC but a bunch of New Yorkers are celebrating at the bit.ly hack.a.bit.

Drew Conway has some ideas how to celebrate.

Ban Ki-Moon’s (UN Secretary General) message(pdf) on World Statistics Day:

On this first World Statistics Day I encourage the international community to work with the United Nations to enable all countries to meet their statistical needs.
 

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Jared Lander is the Chief Data Scientist of Lander Analytics a New York data science firm, Adjunct Professor at Columbia University, Organizer of the New York Open Statistical Programming meetup and the New York and Washington DC R Conferences and author of R for Everyone.

Last night, Harlan Harris and I gave a talk at the NY Predictive Analytics meetup.  Despite the rain there was a good turn out and people seemed to both enjoy and benefit from the presentation.

As requested I have posted the presentation for all to see.  Please feel free to contact me with any questions.  The data and R code are also posted and we will post at least the presentation on the Meetup page.  Everything is also available in one convenient package at GitHub.

Update:  Harlan wrote up a great summary of the night.

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Jared Lander is the Chief Data Scientist of Lander Analytics a New York data science firm, Adjunct Professor at Columbia University, Organizer of the New York Open Statistical Programming meetup and the New York and Washington DC R Conferences and author of R for Everyone.

Tonight I will be giving a talk with Harlan Harris at the Predictive Analytics and Machine Learning Meetup in New York.  It is going to be an introduction to Multilevel Models with examples in R and from previous projects I have worked.

Here’s the details for the talk.

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Jared Lander is the Chief Data Scientist of Lander Analytics a New York data science firm, Adjunct Professor at Columbia University, Organizer of the New York Open Statistical Programming meetup and the New York and Washington DC R Conferences and author of R for Everyone.

A great way to visualize the results of a regression is to use a Coefficient Plot like the one to the right.  I’ve seen people on Twitter asking how to build this and there has been an option available using Andy Gelman’s coefplot() in the arm package.  Not knowing this I built my own (as seen in this post about taste testing tomatoes) and they both suffered the same problems:.  Long coefficient names often got cut off by the left margin of the graph and the name of the variable was appended to all the levels of a factor.  One big difference between his and mine is that his does not include the Intercept by default.  Mine includes the intercept with the option of excluding it.

I managed to solve the latter problem pretty quickly using some regular expressions.  Now the levels of factors are displayed alone, without being prepended by the factor name.  As for the former, I fixed that yesterday by taking advantage of ggplot by Hadley Wickham which deals with the margins better than I do.

Both of these changes made for a vast improvement over what I had avialable before.  Future improvements will address the sorting of the coefficients displayed and allow users to choose their own display names for the coefficients.

The function is in this file and is called plotCoef() and is very customizable, down to the color and line thickness.  I kept my old version, plotCoefBase(), in the file in case some people are adverse to using ggplot, though no one should be.  I sent the code to Dr. Gelman to hopefully be incorporated into his function which I’m sure gets used by a lot more people than mine will.  Examples of my old version and of Dr. Gelman’s are after the break.

As always, any comments or questions are welcomed.  Go to the Contact page or send an email to contact -at- jaredlander -dot- com or find me on Twitter @jaredlander. Continue reading

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Jared Lander is the Chief Data Scientist of Lander Analytics a New York data science firm, Adjunct Professor at Columbia University, Organizer of the New York Open Statistical Programming meetup and the New York and Washington DC R Conferences and author of R for Everyone.

Last week Slice ran a post about a tomato taste test they conducted with Scott Wiener (of Scott’s NYC Pizza Tours), Brooks Jones, Jason Feirman, Nick Sherman and Roberto Caporuscio from Keste.  While the methods used may not be rigorous enough for definitive results, I took the summary data that was in the post and performed some simple analyses.

The first thing to note is that there are only 16 data points, so multiple regression is not an option.  We can all thank the Curse of Dimensionality for that.  So I stuck to simpler methods and visualizations.  If I can get the raw data from Slice, I can get a little more advanced.

For the sake of simplicity I removed the tomatoes from Eataly because their price was such an outlier that it made visualizing the data difficult.  As usual, most of the graphics were made using ggplot2 by Hadley Wickham.  The coefficient plots were made using a little function I wrote.  Here is the code.  Any suggestions for improvement are greatly appreciated, especially if you can help with increasing the left hand margin of the plot.  And as always, all the work was done in R.

The most obvious relationship we want to test is Overall Quality vs. Price.  As can be seen from the scatterplot below with a fitted loess curve, there is not a linear relationship between price and quality.

More after the break. Continue reading

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Jared Lander is the Chief Data Scientist of Lander Analytics a New York data science firm, Adjunct Professor at Columbia University, Organizer of the New York Open Statistical Programming meetup and the New York and Washington DC R Conferences and author of R for Everyone.

Less than a month ago, Drew Conway suggested that our R user group present an analysis of the WikiLeaks data.  In that short time he, Mike Dewar, John Myles White and Harlan Harris have put together a beautiful visualization of attacks in Afghanistan.  The static image you see here has since been animated which is a really nice touch.

Within a few hours of them posting their initial results the work spread across the internet, even getting written up in Wired’s Danger Room.  Today, they got picked up by the New York Times where you can see the animation.

The bulk of the work was, of course, done in R.  I remember talking with them about how they were going to scrape the data from the WikiLeaks documents, but I am not certain how they did it in the end.  As is natural for these guys they made their code available on GitHubso you can recreate their results, after you’ve downloaded the data yourself from WikiLeaks.

Briefly looking at their code I can see they used Hadley Wickham’s ggplot and plyr packages (which are almost standard for most R users) as well as R’s mapping packages.  If you want to learn more about how they did this fantastic job come to the next R Meetup where they will present their findings.

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Jared Lander is the Chief Data Scientist of Lander Analytics a New York data science firm, Adjunct Professor at Columbia University, Organizer of the New York Open Statistical Programming meetup and the New York and Washington DC R Conferences and author of R for Everyone.

A post on Slashdot caught my attention.  It was about a microchip from Lyric Semiconductor that does calculations using analog probabilities instead of digital bits of 1’s and 0’s.

The article says that this will both make flash storage more efficient and make statistical calculations quicker.  I doubt it will help with fitting simple regressions where have a fixed formula, but the first thing that came to mind were Bayesian problems, especially a Markov chain Monte Carlo (MCMC).  Using BUGS to run these simulations can be VERY time consuming, so a faster approach would make the lives of many statisticians much easier.  The article did mention that the chip uses Bayesian NAND gates as opposed to digital NAND gates, but I don’t know how that relates to MCMC’s.

I reached out to my favorite Bayesian, Andy Gelman, to see what he thinks.  I’ll report back on what he says.

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Jared Lander is the Chief Data Scientist of Lander Analytics a New York data science firm, Adjunct Professor at Columbia University, Organizer of the New York Open Statistical Programming meetup and the New York and Washington DC R Conferences and author of R for Everyone.