What makes a statistician look like a hero?

September 19, 2013
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Answer here (courtesy of Kaiser Fung).The post What makes a statistician look like a hero? appeared first on Statistical Modeling, Causal Inference, and Social Science.

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Vanity heights and scary charts

September 19, 2013
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Vanity heights and scary charts

Sometimes I wonder if I should just become a chart doctor. Andrew recently wrote that journals should have graphical editors. Businesses also need those, judging from this submission through Twitter (@francesdonald). Link is here. You don't know whether to laugh...

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Is coffee a killer? I don’t think the effect is as high as was estimated from the highest number that came out of a noisy study

September 19, 2013
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Is coffee a killer?  I don’t think the effect is as high as was estimated from the highest number that came out of a noisy study

Thomas Lumley writes: The Herald has a story about hazards of coffee. The picture caption says Men who drink more than four cups a day are 56 per cent more likely to die. which is obviously not true: deaths, as we’ve observed before, are fixed at one per customer.  The story says It’s not that people […]The post Is coffee a killer? I don’t think the effect is as high as…

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informative hypotheses (book review)

September 18, 2013
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informative hypotheses (book review)

The title of this book Informative Hypotheses somehow put me off from the start: the author, Hebert Hoijtink, seems to distinguish between informative and uninformative (deformative? disinformative?) hypotheses. Namely, something like H0: μ1=μ2=μ3=μ4 is “very informative” and unrealistic, and the alternative Ha is completely uninformative, while the “alternative null” H1: μ1<μ2=μ3<μ4 is informative. (Hence the < […]

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Pseudo-Bayes: a quick and awfully incomplete review

September 18, 2013
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Pseudo-Bayes: a quick and awfully incomplete review

A recently arxived paper by Pier Bissiri, Chris Holmes and Steve Walker piqued my curiosity about “pseudo-Bayesian” approaches, that is, statistical approaches based on a pseudo-posterior: where is some pseudo-likelihood. Pier, Chris and Steve use in particular where is some empirical risk function. A good example is classification; then could be the proportion of properly […]

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How to consume statistical analysis

September 18, 2013
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How to consume statistical analysis

I am giving a talk next week for the Data Science Group in Cambridge.  It's part six of the Leading Analytics series:Building your Analytical Skill setExport Tell a friend ShareTuesday, September 24, 20136:00 PM to 8:00 PMMicrosoft1...

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Understanding posterior p-values

September 18, 2013
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David Kaplan writes: I came across your paper “Understanding Posterior Predictive P-values”, and I have a question regarding your statement “If a posterior predictive p-value is 0.4, say, that means that, if we believe the model, we think there is a 40% chance that tomorrow’s value of T(y_rep) will exceed today’s T(y).” This is perfectly […]The post Understanding posterior p-values appeared first on Statistical Modeling, Causal Inference, and Social Science.

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Compute a contour (level curve) in SAS

September 18, 2013
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Compute a contour (level curve) in SAS

Like many other computer packages, SAS can produce a contour plot that shows the level sets of a function of two variables. For example, I've previously written blogs that use contour plots to visualize the bivariate normal density function and to visualize the cumulative normal distribution function. However, sometimes you [...]

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Two Announcements

September 17, 2013
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Two Announcements

A couple of announcements: First: A message from Jeff Leek: “We are hosting an “unconference” on Google Hangouts. We got some really amazing speakers to talk about the future of statistics. I wonder if you could help advertise the unconference on your blogs. Here is our post: http://simplystatistics.org/2013/09/17/announcing-the-simply-statistics-unconference-on-the-future-of-statistics-futureofstats/ and the sign up page: https://plus.google.com/events/cd94ktf46i1hbi4mbqbbvvga358 We […]

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Two Announcements

September 17, 2013
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Two Announcements

A couple of announcements: First: A message from Jeff Leek: “We are hosting an “unconference” on Google Hangouts. We got some really amazing speakers to talk about the future of statistics. I wonder if you could help advertise the unconference on your blogs. Here is our post: http://simplystatistics.org/2013/09/17/announcing-the-simply-statistics-unconference-on-the-future-of-statistics-futureofstats/ and the sign up page: https://plus.google.com/events/cd94ktf46i1hbi4mbqbbvvga358 We […]

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The Wages of Philosophical Sin are Research Death

September 17, 2013
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The last post about Mayo’s Severity Principle got me thinking about that xkcd cartoon which generated so much hate-and-discontent among Frequentists. I didn’t care for it because all Frequentists can say in response is “we’re not that dumb”; ...

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Online conference for young statistics researchers

September 17, 2013
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Inspired by the Future of Statistical Sciences Workshop (an official event which will be full of middle-aged guys talking about the future), Jeff Leek and Roger Peng have organized a mini-conference in the form of a Google hangout featuring a bunch of youngsters. Seems like a good idea to me! Their particular focus will be […]The post Online conference for young statistics researchers appeared first on Statistical Modeling, Causal Inference,…

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Announcing the Simply Statistics Unconference on the Future of Statistics #futureofstats

September 17, 2013
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Sign up here! We here at Simply Statistics are pumped about the Statistics 2013 Future of Statistical Sciences Workshop (Nov. 11-12). It is a great time to be a statistician and discussing the future of our discipline is of utmost importance … Continue reading →

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Christian Robert on the Jeffreys-Lindley paradox; more generally, it’s good news when philosophical arguments can be transformed into technical modeling issues

September 17, 2013
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X writes: This paper discusses the dual interpretation of the Jeffreys– Lindley’s paradox associated with Bayesian posterior probabilities and Bayes factors, both as a differentiation between frequentist and Bayesian statistics and as a pointer to the difficulty of using improper priors while testing. We stress the considerable impact of this paradox on the foundations of […]The post Christian Robert on the Jeffreys-Lindley paradox; more generally, it’s good news when philosophical…

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Using planel.groups in lattice

September 17, 2013
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Using planel.groups in lattice

Last Tuesday I attended the LondonR user group meeting, where Rich and Andy from Mango argued about the better package for multivariate graphics with R: lattice vs. ggplot2. As part of their talk they had a little competition in visualising London Unde...

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Strategy Metaphors in Soccer

September 17, 2013
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Strategy Metaphors in Soccer

I play football (soccer) every week in a recreational indoor league. While this is a pretty hectic game with no real time to breathe, I've noticed a few patterns that, in the moment, convince me that there should be a...

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Writing Multiple Functions (Introduction to Statistical Computing)

September 17, 2013
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Lecture 5: Using multiple functions to solve multiple problems; to sub-divide awkward problems into more tractable ones; to re-use solutions to recurring problems. Value of consistent interfaces for functions working with the same object, or doing si...

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Lab: Of Big- and Small- Hearted Cats (Introduction to Statistical Computing)

September 17, 2013
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In which we practice the arts of writing functions and of estimating distributions, while contemplating just how little room there is in the heart of a cat. Lab Introduction to Statistical Computing

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Homework: Hitting Bottom and Calling for a Shovel (Introduction to Statistical Computing)

September 17, 2013
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In which we see how to minimize the mean squared error when there are two parameters, in the process learning about writing functions, decomposing problems into smaller steps, testing the solutions to the smaller steps, and minimization by gradient de...

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Top-Down Design (Introduction to Statistical Computing)

September 17, 2013
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Lecture 6: Top-down design is a recursive heuristic for solving problems by writing functions: start with a big-picture view of the problem; break it into a few big sub-problems; figure out how to integrate the solutions to each sub-problem; and then ...

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LaTeX: Itemize and Enumerate

September 17, 2013
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LaTeX: Itemize and Enumerate

Previously, we talk about paragraph, spacing, and indentation. What about listing in $\mathrm{\LaTeX}$?Just like MS Word, $\mathrm{\LaTeX}$ has both bullet and alphanumeric environment for listing. Bullet listing is constructed inside the itemize domai...

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Forecasting with daily data

September 17, 2013
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Forecasting with daily data

I’ve had several emails recently asking how to forecast daily data in R. Unless the time series is very long, the easiest approach is to simply set the frequency attribute to 7. y <- ts(x, frequency=7) Then any of the usual time series forecasting methods should produce reasonable forecasts. For example library(forecast) fit <- ets(y) fc <- forecast(fit) plot(fc) When the time series is long enough to take in more…

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Attendance in parliament (in Italy)

September 16, 2013
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Attendance in parliament (in Italy)

Earlier today, I found some interesting data on Italian MPs voting records in the current parliament (which was opened last April). The data are available for both Houses (the Italian system has a lower house, called Camera $-$ effectively the same as ...

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