Category: Statistics

the beauty of maths in computer science [book review]

CRC Press sent me this book for review in CHANCE: Written by Jun Wu, “staff research scientist in Google who invented Google’s Chinese, Japanese, and Korean Web search algorithms”, and translated from the Chinese, 数学之美, originating from Google blog entries. (Meaning most references are pre-2010.) A large part of the book is about word processing and […]

Causal inference data challenge!

Susan Gruber, Geneviève Lefebvre, Tibor Schuster, and Alexandre Piché write: The ACIC 2019 Data Challenge is Live! Datasets are available for download (no registration required) at https://sites.google.com/view/ACIC2019DataChallenge/data-challenge (bottom of the page). Check out the FAQ at https://sites.google.com/view/ACIC2019DataChallenge/faq The deadline for submitting results is April 15, 2019. The fourth Causal Inference Data Challenge is taking place […]

prepaid ABC

Merijn Mestdagha, Stijn Verdoncka, Kristof Meersa, Tim Loossensa, and Francis Tuerlinckx from the KU Leuven, some of whom I met during a visit to its Wallon counterpart Louvain-La-Neuve, proposed and arXived a new likelihood-free approach based on saving simulations on a large scale for future users. Future users interested in the same model. The very […]

Does Harvard discriminate against Asian Americans in college admissions?

Sharad Goel, Daniel Ho and I looked into the question, in response to a recent lawsuit. We wrote something for the Boston Review: What Statistics Can’t Tell Us in the Fight over Affirmative Action at Harvard Asian Americans and Academics “Distinguishing Excellences” Adjusting and Over-Adjusting for Differences The Evolving Meaning of Merit Character and Bias […]

statistics in Nature [a tale of the two Steves]

In the 29 November issue of Nature, Stephen Senn (formerly at Glasgow) wrote an article about the pitfalls of personalized medicine, for the statistics behind the reasoning are flawed. “What I take issue with is the de facto assumption that the differential response to a drug is consistent for each individual, predictable and based on […]

Storytelling: What’s it good for?

A story can be an effective way to send a message. Anna Clemens explains: Why are stories so powerful? To answer this, we have to go back at least 100,000 years. This is when humans started to speak. For the following roughly 94,000 years, we could only use spoken words to communicate. Stories helped us […]

Markov Chains [not a book review]

As Randal Douc and Éric Moulines are both very close friends and two authors of this book on Markov chains,  I cannot engage into a regular book review! Judging from the table of contents, the coverage is not too dissimilar to the now classic Markov chain Stochastic Stability book by Sean Meyn and the late […]

Coursera course on causal inference from Michael Sobel at Columbia

Here’s the description: This course offers a rigorous mathematical survey of causal inference at the Master’s level. Inferences about causation are of great importance in science, medicine, policy, and business. This course provides an introduction to the statistical literature on causal inference that has emerged in the last 35-40 years and that has revolutionized the […]

John van Neumann (3) vs. Albert Brooks; Paul Erdos advances

We had some good arguments on both sides yesterday. For Erdos, from Diana Senechal: From an environmental perspective, Erdos is the better choice; his surname is an adjectival form of the Hungarian erdő, “forest,” whereas “Carson” clearly means “son of a car.” Granted, the son of a car, being rebellious and all, might prove especially […]

How post-hoc power calculation is like a shit sandwich

Damn. This story makes me so frustrated I can’t even laugh. I can only cry. Here’s the background. A few months ago, Aleksi Reito (who sent me the adorable picture above) pointed me to a short article by Yanik Bababekov, Sahael Stapleton, Jessica Mueller, Zhi Fong, and David Chang in Annals of Surgery, “A Proposal […]

Nature Outlook on AI

The 29 November 2018 issue of Nature had a series of papers on AIs (in its Outlook section). At the general public (awareness) level than in-depth machine-learning article. Including one on the forecasted consequences of ever-growing automation on jobs, quoting from a 2013 paper by Carl Frey and Michael Osborne [of probabilistic numerics fame!] that […]

Stigler’s law of eponymy and human nature

Stigler’s law of eponymy states that no scientific discovery is named after the first person to discover it. Stephen Stigler acknowledged that he was not the first to realize this. Of course this is just an aphorism. Sometimes discoveries are indeed named after their discoverers. But the times when this isn’t the case are more […]