ggformula: another option for teaching graphics in R to beginners

September 21, 2017
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ggformula: another option for teaching graphics in R to beginners

A previous entry (http://sas-and-r.blogspot.com/2017/07/options-for-teaching-r-to-beginners.html) describes an approach to teaching graphics in R that also “get[s] students doing powerful things quickly”, as David Robinson suggested. In t...

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Easy-to-understand Statistics for the Public

September 21, 2017
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Easy-to-understand Statistics for the Public

In a recently published EUROSTAT publication, the authors demand innovative forms of communication from public statistics in order not to lose their socially important role. Among other things, they demand ‘…. to tell stories close to the people; to create communities around specific themes; to develop among citizens the ability to read the data and … Continue reading Easy-to-understand Statistics for the Public

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Monte Carlo Simulations & the "SimDesign" Package in R

September 20, 2017
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Monte Carlo Simulations & the "SimDesign" Package in R

Past posts on this blog have included several relating to Monte Carlo simulation - e.g., see here, here, and here.Recently I came across a great article by Matthew Sigal and Philip Chalmers in the Journal of Statistics Education. It's titled, "Play it ...

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Call for papers: Probabilistic Programming Languages, Semantics, and Systems (PPS 2018)

September 20, 2017
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I’m on the program committee and they say they’re looking to broaden their horizons this year to include systems like Stan. The workshop is part of POPL, the big programming language theory conference. Here’s the official link PPS 2018 home page Call for extended abstracts (2 pages) The submissions are two-page extended abstracts and the […] The post Call for papers: Probabilistic Programming Languages, Semantics, and Systems (PPS 2018) appeared…

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Using black-box machine learning predictions as inputs to a Bayesian analysis

September 20, 2017
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Following up on this discussion [Designing an animal-like brain: black-box “deep learning algorithms” to solve problems, with an (approximately) Bayesian “consciousness” or “executive functioning organ” that attempts to make sense of all these inferences], Mike Betancourt writes: I’m not sure AI (or machine learning) + Bayesian wrapper would address the points raised in the paper. […] The post Using black-box machine learning predictions as inputs to a Bayesian analysis appeared…

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Quantifying privacy loss in a statistical database

September 20, 2017
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Quantifying privacy loss in a statistical database

In the previous post we looked at a simple randomization procedure to obscure individual responses to yes/no questions in a way that retains the statistical usefulness of the data. In this post we’ll generalize that procedure, quantify the privacy loss, and discuss the utility/privacy trade-off. More general randomized response Suppose we have a binary response […]

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Fisher’s transformation of the correlation coefficient

September 20, 2017
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Fisher’s transformation of the correlation coefficient

Pearson's correlation measures the linear association between two variables. Because the correlation is bounded between [-1, 1], the sampling distribution for highly correlated variables is highly skewed. Even for bivariate normal data, the skewness makes it challenging to estimate confidence intervals for the correlation, to run one-sample hypothesis tests ("Is [...] The post Fisher's transformation of the correlation coefficient appeared first on The DO Loop.

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Recording Podcasts with a Remote Co-Host

September 20, 2017
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Recording Podcasts with a Remote Co-Host

I previously wrote about my editing workflow for podcasts and I thought I’d follow up with some details on how I record both Not So Standard Deviations and The Effort Report. This post is again going to be a bit Mac-specific because, well, that...

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p less than 0.00000000000000000000000000000000 . . . now that’s what I call evidence!

September 19, 2017
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I read more carefully the news article linked to in the previous post, which describes a forking-pathed nightmare of a psychology study, the sort of thing that was routine practice back in 2010 or so but which we’ve mostly learned to at least try to avoid. Anyway, one thing I learned there’s something called “terror […] The post p less than 0.00000000000000000000000000000000 . . . now that’s what I call…

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Stan Course in Newcastle, United Kingdom!

September 19, 2017
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(this post is by Betancourt) The growth of Stan has afforded the core team many opportunities to give courses, to both industrial and academic audiences and at venues  across the world.  Regrettably we’re not always able to keep up with demand for new courses, especially outside of the United States, due to our already busy schedules. […] The post Stan Course in Newcastle, United Kingdom! appeared first on Statistical Modeling, Causal…

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As if the 2010s never happened

September 19, 2017
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E. J. writes: I’m sure I’m not the first to send you this beauty. Actually, E. J., you’re the only one who sent me this! It’s a news article, “Can the fear of death instantly make you a better athlete?”, reporting on a psychology experiment: For the first study, 31 male undergraduates who liked basketball […] The post As if the 2010s never happened appeared first on Statistical Modeling, Causal…

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Getting into the head of the chart designer

September 19, 2017
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Getting into the head of the chart designer

Kaiser Fung, creator of Junk Charts and Principal Analytics Prep, shows that maps are not the only way to deliver insights about geographical data.

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Randomized response, privacy, and Bayes theorem

September 19, 2017
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Randomized response, privacy, and Bayes theorem

Suppose you want to gather data on an incriminating question. For example, maybe a statistics professor would like to know how many students cheated on a test. Being a statistician, the professor has a clever way to find out what he wants to know while giving each student deniability. Randomized response Each student is asked […]

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Review: Putting Stories to Work and Out On the Wire

September 19, 2017
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Review: Putting Stories to Work and Out On the Wire

Two books I’ve read recently make good points about stories that apply to data stories, without the books being about data: Shawn Callahan’s Putting Stories to Work and Jessica Abel’s Out On the Wire. Strategic Use of Stories In Putting Stories to Work, Shawn Callahan has a very pragmatic view of how stories can be […]

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One Little Thing: knitr::fig_chunk()

During the dark days when I still enjoyed wrestling with LaTeX, I had a little problem when I was using knitr to generate figures automatically: I didn’t want the plots to be placed in the middle of R source code (the default behavior of knitr), but in separate figure environments outside the code chunks. For example, for a code chunk below: plot(cars) summary(cars) I can only insert it in a…

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Maybe this paper is a parody, maybe it’s a semibluff

September 18, 2017
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Peter DeScioli writes: I was wondering if you saw this paper about people reading Harry Potter and then disliking Trump, attached. It seems to fit the shark attack genre. In this case, the issue seems to be judging causation from multiple regression with observational data, assuming that control variables are enough to narrow down to […] The post Maybe this paper is a parody, maybe it’s a semibluff appeared first…

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The path of zip codes

September 18, 2017
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The path of zip codes

Toe bone connected to the foot bone, Foot bone connected to the leg bone, Leg bone connected to the knee bone,...              — American Spiritual, "Dem Bones" Last week I read an interesting article on Robert Kosara's data visualization blog. Kosara connected the geographic centers of the US zip codes in [...] The post The path of zip codes appeared first on The DO Loop.

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The Good, the Bad and the Ugly

September 18, 2017
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The Good, the Bad and the Ugly

Communication of statistics in times of fake news In a recent paper Emanuele Baldacci, (Director, Eurostat) and Felicia Pelagalli, (President, InnovaFiducia) deal with the ‘challenges for official statistics of changes in the information market spurred by network technology, data revolution and changes in information consumers’ behaviours’ (p.3) Three scenarios The status-quo or bad scenario: ‘Information will continue to … Continue reading The Good, the Bad and the Ugly

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Political polls – why they work – or don’t

September 18, 2017
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Political polls – why they work – or don’t

Political polls – why do they work – or don’t This is written in the week before the 2017 New Zealand General Election and it is an exciting time. Many New Zealanders are finding political polls fascinating right now. We … Continue reading →

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The Minimal Reproducible Example Paradox

The Minimal Reproducible Example Paradox

How many times have I reminded a user of posting a minimal, self-contained, and reproducible example (reprex)? Probably 500 times. How many times do I think I will still need to remind users of this? Perhaps 5000 times. I think there is a paradox, and there isn’t a clever solution. The paradox is that we software developers know much more about our own software than average users (especially beginners), and…

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Editing Podcasts with Logic Pro X

September 18, 2017
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Editing Podcasts with Logic Pro X

I thought I’d write a brief description of how I edit podcasts using Logic Pro X because when I was first getting into podcasts, I didn’t find a lot of useful stuff out there. A lot of it was YouTube videos of advanced editing or very bas...

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Unbiased Hamiltonian Monte Carlo with couplings

September 17, 2017
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Unbiased Hamiltonian Monte Carlo with couplings

With Jeremy Heng we have recently arXived a paper describing how to remove the burn-in bias of Hamiltonian Monte Carlo (HMC). This follows a recent work on unbiased MCMC estimators in general on which I blogged here. The case of HMC requires a specific yet very simple coupling. A direct consequence of this work is that Hamiltonian Monte […]

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Machine Learning Meets Central Banking

September 17, 2017
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Machine Learning Meets Central Banking

Here's a nice new working paper from the Bank of England.  There's nothing new methodologically, but there are three fascinating and detailed applications / case studies (banking supervision under imperfect information, UK CPI inflation forecastin...

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