Category: Statistics

Surprise-hacking: “the narrative of blindness and illusion sells, and therefore continues to be the central thesis of popular books written by psychologists and cognitive scientists”

Teppo Felin sends along this article with Mia Felin, Joachim Krueger, and Jan Koenderink on “surprise-hacking,” and writes: We essentially see surprise-hacking as the upstream, theoretical cousin of p-hacking. Though, surprise-hacking can’t be resolved with replication, more data or preregistration. We use perception and priming research to make these points (linking to Kahneman and priming, […]

The post Surprise-hacking: “the narrative of blindness and illusion sells, and therefore continues to be the central thesis of popular books written by psychologists and cognitive scientists” appeared first on Statistical Modeling, Causal Inference, and Social Science.

Surprise-hacking: “the narrative of blindness and illusion sells, and therefore continues to be the central thesis of popular books written by psychologists and cognitive scientists”

Teppo Felin sends along this article with Mia Felin, Joachim Krueger, and Jan Koenderink on “surprise-hacking,” and writes: We essentially see surprise-hacking as the upstream, theoretical cousin of p-hacking. Though, surprise-hacking can’t be resolved with replication, more data or preregistration. We use perception and priming research to make these points (linking to Kahneman and priming, […]

The post Surprise-hacking: “the narrative of blindness and illusion sells, and therefore continues to be the central thesis of popular books written by psychologists and cognitive scientists” appeared first on Statistical Modeling, Causal Inference, and Social Science.

“My advisor and I disagree on how we should carry out repeated cross-validation. We would love to have a third expert opinion…”

Youyou Wu writes: I’m a postdoc studying scientific reproducibility. I have a machine learning question that I desperately need your help with. My advisor and I disagree on how we should carry out repeated cross-validation. We would love to have a third expert opinion… I’m trying to predict whether a study can be successfully replicated […]

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How we should they carry out repeated cross-validation? They would like a third expert opinion…”

Someone writes: I’m a postdoc studying scientific reproducibility. I have a machine learning question that I desperately need your help with. . . . I’m trying to predict whether a study can be successfully replicated (DV), from the texts in the original published article. Our hypothesis is that language contains useful signals in distinguishing reproducible […]

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A couple of thoughts regarding the hot hand fallacy fallacy

For many years we all believed the hot hand was a fallacy. It turns out we were all wrong. Fine. Such reversals happen. Anyway, now that we know the score, we can reflect on some of the cognitive biases that led us to stick with the “hot hand fallacy” story for so long. Jason Collins […]

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A couple of thoughts regarding the hot hand fallacy fallacy

For many years we all believed the hot hand was a fallacy. It turns out we were all wrong. Fine. Such reversals happen. Anyway, now that we know the score, we can reflect on some of the cognitive biases that led us to stick with the “hot hand fallacy” story for so long. Jason Collins […]

The post A couple of thoughts regarding the hot hand fallacy fallacy appeared first on Statistical Modeling, Causal Inference, and Social Science.

Reusable Pipelines in R

Pipelines in R are popular, the most popular one being magrittr as used by dplyr. This note will discuss the advanced re-usable piping systems: rquery/rqdatatable operator trees and wrapr function object pipelines. In each case we have a set of objects designed to extract extra power from the wrapr dot-arrow pipe %.>%. Piping Piping is … Continue reading Reusable Pipelines in R

Oh, I hate it when work is criticized (or, in this case, fails in attempted replications) and then the original researchers don’t even consider the possibility that maybe in their original work they were inadvertently just finding patterns in noise.

I have a sad story for you today. Jason Collins tells it: In The (Honest) Truth About Dishonesty, Dan Ariely describes an experiment to determine how much people cheat . . . The question then becomes how to reduce cheating. Ariely describes one idea: We took a group of 450 participants and split them into […]

The post Oh, I hate it when work is criticized (or, in this case, fails in attempted replications) and then the original researchers don’t even consider the possibility that maybe in their original work they were inadvertently just finding patterns in noise. appeared first on Statistical Modeling, Causal Inference, and Social Science.

Oh, I hate it when work is criticized (or, in this case, fails in attempted replications) and then the original researchers don’t even consider the possibility that maybe in their original work they were inadvertently just finding patterns in noise.

I have a sad story for you today. Jason Collins tells it: In The (Honest) Truth About Dishonesty, Dan Ariely describes an experiment to determine how much people cheat . . . The question then becomes how to reduce cheating. Ariely describes one idea: We took a group of 450 participants and split them into […]

The post Oh, I hate it when work is criticized (or, in this case, fails in attempted replications) and then the original researchers don’t even consider the possibility that maybe in their original work they were inadvertently just finding patterns in noise. appeared first on Statistical Modeling, Causal Inference, and Social Science.

RSA with Pseudoprimes

RSA setup Recall the setup for RSA encryption given in the previous post. Select two very large prime numbers p and q. Compute n = pq and φ(n) = (p – 1)(q – 1). Choose an encryption key e relatively prime to φ(n). Calculate the decryption key d such that ed = 1 (mod φ(n)). Publish e and n, and keep d, p, and q secret. φ is Euler’s totient function, defined here. There’s a complication in the first […]

Can I have the last four digits of your social?

Imagine this conversation. “Could you tell me your social security number?” “Absolutely not! That’s private.” “OK, how about just the last four digits?” “Oh, OK. That’s fine.” When I was in college, professors would post grades by the last four digits of student social security numbers. Now that seems incredibly naive, but no one objected […]

Time series of Democratic/Republican vote share in House elections

Yair prepared this graph of average district vote (imputing open seats at 75%/25%; see here for further discussion of this issue) for each House election year since 1976: Decades of Democratic dominance persisted through 1992; since then the two parties have been about even. As has been widely reported, a mixture of geographic factors and […]

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Time series of Democratic/Republican vote share in House elections

Yair prepared this graph of average district vote (imputing open seats at 75%/25%; see here for further discussion of this issue) for each House election year since 1976: Decades of Democratic dominance persisted through 1992; since then the two parties have been about even. As has been widely reported, a mixture of geographic factors and […]

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RSA encryption exponents are mostly all the same

The big idea of public key cryptography is that it lets you publish an encryption key e without compromising your decryption key d. A somewhat surprising detail of RSA public key cryptography is that in practice e is nearly always the same number, specifically e = 65537. We will review RSA, explain how this default e was chosen, and discuss why […]

Revealing information by trying to suppress it

FAS posted an article yesterday explaining how blurring military installations out of satellite photos points draws attention to them, showing exactly where they are and how big they are. The Russian mapping service Yandex Maps blurred out sensitive locations in Israel and Turkey. As the article says, this is an example of the Streisand effect, […]

“Do you have any recommendations for useful priors when datasets are small?”

A statistician who works in the pharmaceutical industry writes: I just read your paper (with Dan Simpson and Mike Betancourt) “The Prior Can Often Only Be Understood in the Context of the Likelihood” and I find it refreshing to read that “the practical utility of a prior distribution within a given analysis then depends critically […]

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