Announcing the Release of swirl 2.0

January 28, 2014
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Editor's note: This post was written by Nick Carchedi, a Master's degree student in the Department of Biostatistics at Johns Hopkins. He is working with us to develop the Data Science Specialization as well as software for interactive learning of … Continue reading →

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Defining Properly MA(∞) Time Series

January 28, 2014
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Defining Properly MA(∞) Time Series

In order to properly define series, we need to get back on some properties of infinite sequences, as briefly mentioned yesterday in the MAT8181 course. Consider some sequence . The sequence is said to be summable if is convergent, i.e. if the limit of  exists when . From Cauchy criterion,  converges if and only if for each , there is  for which when . The sequence  is said to be…

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History is too important to be left to the history professors

January 28, 2014
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From Thomas Laqueur, the Helen Fawcett professor of history at the University of California, reviewing a book by Christopher Clark: [As of 6 July 1914, the German] army made no plans for a general war; the kaiser believed the war would be localized. . . . A last small chance at least to contain a […]The post History is too important to be left to the history professors appeared first…

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Marie Curie says stop hating on quilt plots already.

January 28, 2014
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Marie Curie says stop hating on quilt plots already.

"There are sadistic scientists who hurry to hunt down error instead of establishing the truth." -Marie Curie (http://en.wikiquote.org/wiki/Marie_Curie) Thanks to Kasper H. for that quote. I think it is a perfect fit for today's culture of academic put down as … Continue reading →

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Video Tutorial: Breaking Down the Definition of the Hazard Function

Video Tutorial: Breaking Down the Definition of the Hazard Function

The hazard function is a fundamental quantity in survival analysis.  For an event occurring at some time on a continuous time scale, the hazard function, , for that event is defined as , where is the time, is the time of the occurrence of the event. However, what does this actually mean?  In this Youtube […]

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Using Last.fm to data mine my music listening history

January 28, 2014
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Using Last.fm to data mine my music listening history

I've (passively) been keeping meticulous records of almost every song I've listened to since January of 2008. Since I opened my last.fm account 6 years ago, they've accumulated a massive detailed dataset of the 107,222 songs I've listened to since then. The best thing is that they're willing to share this data with me! I »more

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Online collaborative writing

January 28, 2014
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Online collaborative writing

Everyone who has written a paper with another author will know it can be tricky making sure you don’t end up with two versions that need to be merged. The good news is that the days of sending updated drafts by email backwards and forwards is finally over (having lasted all of 25 years — I can barely imagine writing papers before email). LaTeX solutions There has been a lot…

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“Disappointed with your results? Boost your scientific paper”

January 27, 2014
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“Disappointed with your results?  Boost your scientific paper”

This, sent in by Ben Bolker, is just tooooo funny. Click on the above image to see more clearly. In addition to the quote I used in the above title, there’s also this: +10.000 correlations/min Sooner than later, your future discovery will pop up. and this: The most relevant conclusions in your scientific paper are […]The post “Disappointed with your results? Boost your scientific paper” appeared first on Statistical Modeling,…

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Best blog comment ever

January 27, 2014
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Best blog comment ever

Go here and scroll down to the comment by “hokiesuck.” P.S. Some people report that they can’t get to the comments on the Monkey Cage blog, so I’ll repost it here: The post Best blog comment ever appeared first on Statistical...

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Introducing the statistical parable

January 27, 2014
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Last week, Andrew Gelman (link) and I were kindred spirits: we both did a "numbersensing" exercise on two different data analyses. I was reading the MailChimp study on the effect of Google siphoning off "marketing" emails into a separate tab, and a noise buzzed my head when I saw that the aggregate click-to-open ratio was reported at an inconceivable 85%. (See Part 1 of my reaction here.) In the meantime,…

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Ulam spirals: Visualizing properties of prime numbers with SAS

January 27, 2014
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Ulam spirals: Visualizing properties of prime numbers with SAS

Prime numbers are strange beasts. They exhibit properties of both randomness and regularity. Recently I watched an excellent nine-minute video on the Numberphile video blog that shows that if you write the natural numbers in a spiral pattern (called the Ulam spiral), then there are certain lines in the pattern [...]

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Data Stories Podcast: 2013 in Review, Outlook to 2014

January 27, 2014
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Data Stories Podcast: 2013 in Review, Outlook to 2014

The Data Stories podcast starts the new year with Andy Kirk and me as guests. With the hosts, Enrico Bertini and Moritz Stefaner, we discuss the major developments of 2013 and look ahead to what 2014 has in store. You can listen to the podcast episode directly on its page, but you should really subscribe […]

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New in forecast 5.0

January 27, 2014
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New in forecast 5.0

Last week, version 5.0 of the forecast package for R was released. There are a few new functions and changes made to the package, which is why I increased the version number to 5.0. Thanks to Earo Wang for helping with this new version. Handling missing values and outliers Data cleaning is often the first step that data scientists and analysts take to ensure statistical modelling is supported by good…

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Twitter sucks, and people are gullible as f…

January 26, 2014
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Hey, and I did it in less than 140 characters! The above was my response to this item which David Hogg forwarded to me. The next thing you know, people are going to claim that women are three times as likely to wear red pink when . . . Naaah, forget about it, that would […]The post Twitter sucks, and people are gullible as f… appeared first on Statistical Modeling,…

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Soccer Intervention, A Story in Semi-Demi Hierarchical Models with a Different Number of Hierarchies in Treatment and Control

January 26, 2014
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Was doing a data analysis and power calculation for a proposed group randomized study, and came across an interesting feature where the resulting model for the data will necessarily be different for treatment and control. Treatment will have 3 hierarch...

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Infoviz on top of stat graphic on top of spreadsheet

January 26, 2014
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Infoviz on top of stat graphic on top of spreadsheet

Kaiser points to this infoviz from MIT’s Technology Review: Kaiser writes: What makes the designer want to tilt the reader’s head? This chart is unreadable. It also fails the self-sufficiency test. All 13 data points are printed onto the chart. You really don’t need the axis, and the gridlines. A further design flaw is the […]The post Infoviz on top of stat graphic on top of spreadsheet appeared first on…

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Tuning optim with parscale

January 26, 2014
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I often get questions what is the use of parscale parameter in optim procedure in GNU R. Therefore I have decided to write a simple example showing its usage and importance. The function I test is a simplified version of estimation problem I had to sol...

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Converting plots to data II

January 26, 2014
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Converting plots to data II

There were quite some reactions on lasts week's post converting plots to data. Two additional programs were mentioned; WebPlotDigitzier and DataThief. Note that google or wikipedia has a bunch of alternatives. Datathief is shareware, a java program, so...

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Alexander Aitken

January 26, 2014
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Alexander Aitken

Alexander Aitken was one of New Zealand's greatest mathematicians - see my earlier post. As an econometrician, you may be very surprised how much you owe him!Want to check out more about this amazing man? See www.nzedge.com/alexander-aitken/ .© 2014, ...

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Introduction to the particle Gibbs sampler

January 25, 2014
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Introduction to the particle Gibbs sampler

Introduction Particle MCMC (the use of approximate SMC proposals within exact MCMC algorithms) is arguably one of the most important developments in computational Bayesian inference of the 21st Century. The key concepts underlying these methods are described in a famously impenetrable “read paper” by Andrieu et al (2010). Probably the most generally useful method outlined […]

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Introduction to the particle Gibbs sampler

January 25, 2014
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Introduction to the particle Gibbs sampler

Introduction Particle MCMC (the use of approximate SMC proposals within exact MCMC algorithms) is arguably one of the most important developments in computational Bayesian inference of the 21st Century. The key concepts underlying these methods are described in a famously impenetrable “read paper” by Andrieu et al (2010). Probably the most generally useful method outlined […]

Read more »

Big Data Events

January 25, 2014
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Big Data Events

The Big Data discussion builds momentum in Official Statistics. In October 2012 at the UNECE High-level Seminar on Modernization of Statistical …Continue reading →

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Big Data Events

January 25, 2014
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Big Data Events

The Big Data discussion builds momentum in Official Statistics. In October 2012 at the UNECE High-level Seminar on Modernization of Statistical …Continue reading →

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