Noise noise noise noise noise

March 21, 2016
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Noise noise noise noise noise

An intersting issue came up in comments to yesterday’s post. The story began with this query from David Shor: Suppose you’re conducting an experiment on the effectiveness of a pain medication, but in the post survey, measure a large number of indicators of well being (Sleep quality, self reported pain, ability to get tasks done, […] The post Noise noise noise noise noise appeared first on Statistical Modeling, Causal Inference,…

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On deck this week

March 21, 2016
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Happy spring! Mon: Noise noise noise noise noise Tues: Thinking about this beautiful text sentiment visualizer yields a surprising insight about statistical graphics Wed: In defense of endless arguments Thurs: Multilevel regression Fri: Data-depen...

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Delegate maps need a color treatment

March 21, 2016
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Delegate maps need a color treatment

This year's U.S. primary elections have been very entertaining. Delegate maps are a handy way to keep track of the horse race. They provide data to support (or refute) the narratives created by reporters who use words like "landslide", "commanding",...

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A statistical analysis of Stephen Curry’s shooting

March 21, 2016
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A statistical analysis of Stephen Curry’s shooting

Last week Robert Allison showed how to download NBA data into SAS and create graphs such as the location where Stephen Curry took shots in the 2015-16 season to date. The graph at left shows the kind of graphs that Robert created. I've reversed the colors from Robert's version, so […] The post A statistical analysis of Stephen Curry's shooting appeared first on The DO Loop.

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The Two-Paper Package

March 21, 2016
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The Two-Paper Package

Much of academic work is focused on writing papers. This doesn’t just include the work that goes into the research and the writing, but also strategy – beyond the single paper. Here is one that worked. Even if it’s a bit coincidental, I think it’s a good model for other papers. It’s fairly unusual to talk about … Continue reading The Two-Paper Package

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rOpenSci unconference in Brisbane, 21-22 April 2016

rOpenSci unconference in Brisbane, 21-22 April 2016

The first rOpenSci unconference in Australia will be held on Thursday and Friday (April 21-22) in Brisbane, at the Microsoft Innovation Centre. This event will bring together researchers, developers, data scientists and open data enthusiasts from ind...

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The Evolution of a Data Scientist

March 21, 2016
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The Evolution of a Data Scientist

Editor’s note: This post is a guest post by Andrew Jaffe “How do you get to Carnegie Hall? Practice, practice, practice.” (“The Wit Parade” by E.E. Kenyon on March 13, 1955) ”..an extraordinarily consistent answer in an incredible number ...

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My quick answer is that I would analyze all 10 outcomes using a multilevel model.

March 20, 2016
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David Shor writes: Suppose you’re conducting an experiment on the effectiveness of a pain medication, but in the post survey, measure a large number of indicators of well being (Sleep quality, self reported pain, ability to get tasks done, anxiety levels, etc). After the experiment, the results are insignificant (or the posterior effect size isn’t […] The post My quick answer is that I would analyze all 10 outcomes using…

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Your chance to continue the “due to chance” discussion in roomier quarters

March 19, 2016
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Your chance to continue the “due to chance” discussion in roomier quarters

Comments get unwieldy after 100, so here’s a chance to continue the “due to chance” discussion in some roomier quarters. (There seems to be at least two distinct lanes being travelled.) Now one of the main reasons I run this blog is to discover potential clues to solving or making progress on thorny philosophical problems I’ve been wrangling with for a […]

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Actually, I’d just do full Bayes

March 19, 2016
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Dave Clark writes: I was hoping for your opinion on a topic related to hierarchical models. I am an actuary and have generally worked with the concept of hierarchical models in the context of credibility theory. The text by Bühlmann and Gisler (A Course in Credibility Theory; Springer) sets up the mixed models under the […] The post Actually, I’d just do full Bayes appeared first on Statistical Modeling, Causal…

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Le Monde puzzle [#952]

March 18, 2016
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Le Monde puzzle [#952]

A quite simple Le Monde mathematical puzzle again with Alice and Bob: In a multiple choice questionnaire with 50 questions, Alice gets a score s such that Bob can guess how many correct (+5 points), incorrect (-1 point) and missing (0 point) Alice got when adding that Alice could not have gotten s-2 or s+2. […]

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Le Monde puzzle [#952]

March 18, 2016
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Le Monde puzzle [#952]

A quite simple Le Monde mathematical puzzle again with Alice and Bob: In a multiple choice questionnaire with 50 questions, Alice gets a score s such that Bob can guess how many correct (+5 points), incorrect (-1 point) and missing (0 point) Alice got when adding that Alice could not have gotten s-2 or s+2. […]

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More on preparing data

March 18, 2016
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More on preparing data

The Microsoft Data Science User Group just sponsored Dr. Nina Zumel‘s presentation “Preparing Data for Analysis Using R”. Microsoft saw Win-Vector LLC‘s ODSC West 2015 presentation “Prepping Data for Analysis using R” and generously offered to sponsor improving it and disseminating it to a wider audience. We feel Nina really hit the ball out of … Continue reading More on preparing data

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I definitely wouldn’t frame it as “To determine if the time series has a change-point or not.” The time series, whatever it is, has a change point at every time. The question might be, “Is a change point necessary to model these data?” That’s a question I could get behind.

March 18, 2016
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From the Stan users list: I’m trying out to fit a time series that can have 0 or 1 change point using the sample model from Ch 11.2 of the manual. To determine if the time series has a change-point or not, would I need to do comparison model (via loo) between 1-change model developed […] The post I definitely wouldn’t frame it as “To determine if the time series…

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Light entertainment: March Madness and Wheel of Fortune

March 18, 2016
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Light entertainment: March Madness and Wheel of Fortune

March Madness (via Business Insider): Wheel of Fortune:

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The retreat from religion is accelerating

March 18, 2016
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The retreat from religion is accelerating

Updated results from the CIRP Freshman Survey were published last week, which means it's time for me to update to my annual series on the increasing number of college students with no religious affiliation (the "nones").Since I started following this t...

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R in Insurance: Abstract submission closes end of March

March 18, 2016
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R in Insurance: Abstract submission closes end of March

Hurry! The abstract submission deadline for the 4th R in Insurance conference in London, 11 July 2016 is approaching soon. You have until the 28th of March to submit a one-page abstract for consideration. Both academic and practitioner proposals relate...

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Stan Case Studies Launches

March 18, 2016
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Stan Case Studies Launches

There’s a new section of the Stan web site, with case studies meant to illustrate statistical methodologies, classes of models, application areas, statistical computation, and Stan programming. Stan Case Studies The first ten or so are up, including a grab bag of education models from Daniel Furr at U.C. Berkeley: Hierarchical Two-Parameter Logistic Item Response […] The post Stan Case Studies Launches appeared first on Statistical Modeling, Causal Inference, and…

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Kalesan, Fagan, and Galea respond to criticism of their paper on gun laws and deaths

March 17, 2016
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The other day we posted some remarks on a recent paper by Bindu Kalesan, Jeffrey Fagan, Sandro Galea, “Firearm legislation and firearm mortality in the USA: a cross-sectional, state-level study.” In response to the criticisms from me and various commenters, the authors of the paper prepared a detailed response, which I’m linking to here. They […] The post Kalesan, Fagan, and Galea respond to criticism of their paper on gun…

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Swimsuit special: “A pure Bayesian or pure non-Bayesian is not forever doomed to use out-of-date methods, but at any given time the purist will be missing some of the most effective current techniques.”

March 17, 2016
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Joshua Vogelstein points me to this paper by Gerd Gigerenzer and Julian Marewski, who write: The idol of a universal method for scientific inference has been worshipped since the “inference revolution” of the 1950s. Because no such method has ever been found, surrogates have been created, most notably the quest for significant p values. This […] The post Swimsuit special: “A pure Bayesian or pure non-Bayesian is not forever doomed…

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Lack of free lunch again rears ugly head

March 16, 2016
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We had some discussion on blog the other day of prior distributions in settings such as small experiments where available data do not give a strong inference on their own, and commenter Rahul wrote: In real settings I rarely see experts agree anywhere close to a consensus about the prior. Estimates are all over the […] The post Lack of free lunch again rears ugly head appeared first on Statistical…

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Simulate from the multinomial distribution in the SAS DATA step

March 16, 2016
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Simulate from the multinomial distribution in the SAS DATA step

There are several ways to simulate multinomial data in SAS. In the SAS/IML matrix language, you can use the RANDMULTINOMIAL function to generate samples from the multinomial distribution. If you don't have a SAS/IML license, I have previously written about how to use the SAS DATA step or PROC SURVEYSELECT […] The post Simulate from the multinomial distribution in the SAS DATA step appeared first on The DO Loop.

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Stan backronym just a joke

March 15, 2016
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Stan is named after Stanislaw Ulam, the inventor of the Monte Carlo method. At one point we were joking around and I came up with the backronym Sampling Through Adaptive Neighborhoods. I kinda like this as a backronym but it was really just a joke. Stan does not stand for Sampling Through Adaptive Neighborhoods. Stan […] The post Stan backronym just a joke appeared first on Statistical Modeling, Causal Inference,…

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