andrew_gelman_stats andrew_gelman_stats-2010 andrew_gelman_stats-2010-207 knowledge-graph by maker-knowledge-mining
Source: html
Introduction: A few months ago I questioned Dan Ariely’s belief that Google is the voice of the people by reporting the following bizarre options that Google gave to complete the simplest search I could think of: Several commenters gave informed discussions about what was going on in Google’s program. Maybe things are better now, though? The latest version seems much more reasonable: (Aleks sent this to me, then I checked on my own computer and got the same thing.)
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1 The latest version seems much more reasonable: (Aleks sent this to me, then I checked on my own computer and got the same thing. [sent-3, score-0.949]
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same-blog 1 1.0 207 andrew gelman stats-2010-08-14-Pourquoi Google search est devenu plus raisonnable?
Introduction: A few months ago I questioned Dan Ariely’s belief that Google is the voice of the people by reporting the following bizarre options that Google gave to complete the simplest search I could think of: Several commenters gave informed discussions about what was going on in Google’s program. Maybe things are better now, though? The latest version seems much more reasonable: (Aleks sent this to me, then I checked on my own computer and got the same thing.)
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Introduction: Speaking of open data and google tools, see this post from Revolution R: How to use a Google Spreadsheet as data in R .
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Introduction: Aleks sent me this (I’m not sure from where):
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Introduction: Aleks pointed me to this .
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Introduction: Eric Loken writes : If you’re used to Google upending conventional wisdom, then yesterday’s interview with Laszlo Bock in the New York Times did not disappoint. Google has determined that test scores and transcripts are useless because they don’t predict performance among its employees. . . . I [Loken] am going to assume they’re well aware of the limits of their claim, and instead I’m going say that as readers of the interview we should not lose sight of a fundamental fact - Across a wide variety of employment settings, one of the most robust findings in organizational psychology is that tests of cognitive ability are strong predictors of job performance. If Google has found otherwise, what they have found is that grades and test scores are not predictive of performance at Google. In general, in the workplace tests are still highly predictive of success. If all the research says that test scores and grades predict performance, why would the people at Google want to igno
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same-blog 1 0.96995676 207 andrew gelman stats-2010-08-14-Pourquoi Google search est devenu plus raisonnable?
Introduction: A few months ago I questioned Dan Ariely’s belief that Google is the voice of the people by reporting the following bizarre options that Google gave to complete the simplest search I could think of: Several commenters gave informed discussions about what was going on in Google’s program. Maybe things are better now, though? The latest version seems much more reasonable: (Aleks sent this to me, then I checked on my own computer and got the same thing.)
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Introduction: Aleks sent me this (I’m not sure from where):
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Introduction: I have no idea what this and this are, but Aleks passed these on, and maybe some of you will find them interesting.
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Introduction: Aleks points us to this idea of labeling for news.
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Introduction: Aleks pointed me to this .
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same-blog 1 0.96387446 207 andrew gelman stats-2010-08-14-Pourquoi Google search est devenu plus raisonnable?
Introduction: A few months ago I questioned Dan Ariely’s belief that Google is the voice of the people by reporting the following bizarre options that Google gave to complete the simplest search I could think of: Several commenters gave informed discussions about what was going on in Google’s program. Maybe things are better now, though? The latest version seems much more reasonable: (Aleks sent this to me, then I checked on my own computer and got the same thing.)
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Introduction: Joshua Hartshorne writes: I ran several large-N experiments (separate participants) and looked at performance against age. What we want to do is compare age-of-peak-performance across the different tasks (again, different participants). We bootstrapped age-of-peak-performance. On each iteration, we sampled (with replacement) the X scores at each age, where X=num of participants at that age, and recorded the age at which performance peaked on that task. We then recorded the age at which performance was at peak and repeated. Once we had distributions of age-of-peak-performance, we used the means and SDs to calculate t-statistics to compare the results across different tasks. For graphical presentation, we used medians, interquartile ranges, and 95% confidence intervals (based on the distributions: the range within which 75% and 95% of the bootstrapped peaks appeared). While a number of people we consulted with thought this made a lot of sense, one reviewer of the paper insist
Introduction: As I’ve written here many times, my experiences in social science and public health research have left me skeptical of statistical methods that hypothesize or try to detect zero relationships between observational data (see, for example, the discussion starting at the bottom of page 960 in my review of causal inference in the American Journal of Sociology). In short, I have a taste for continuous rather than discrete models. As discussed in the above-linked article (with respect to the writings of cognitive scientist Steven Sloman), I think that common-sense thinking about causal inference can often mislead. In many cases, I have found that that the theoretical frameworks of instrumental variables and potential outcomes (for a review see, for example, chapters 9 and 10 of my book with Jennifer) help clarify my thinking. Here is an example that came up in a recent blog discussion. Computer science student Elias Bareinboim gave the following example: “suppose we know nothing a
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Introduction: Richard McElreath writes: I’ve been translating a few ongoing data analysis projects into Stan code, mostly with success. The most important for me right now has been a hierarchical zero-inflated gamma problem. This a “hurdle” model, in which a bernoulli GLM produces zeros/nonzeros, and then a gamma GLM produces the nonzero values, using varying effects correlated with those in the bernoulli process. The data are 20 years of human foraging returns from a subsistence hunting population in Paraguay (the Ache), comprising about 15k hunts in total (Hill & Kintigh. 2009. Current Anthropology 50:369-377). Observed values are kilograms of meat returned to camp. The more complex models contain a 147-by-9 matrix of varying effects (147 unique hunters), as well as imputation of missing values. Originally, I had written the sampler myself in raw R code. It was very slow, but I knew what it was doing at least. Just before Stan version 1.0 was released, I had managed to get JAGS to do it a
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Introduction: Radford writes : The word “conservative” gets used many ways, for various political purposes, but I would take it’s basic meaning to be someone who thinks there’s a lot of wisdom in traditional ways of doing things, even if we don’t understand exactly why those ways are good, so we should be reluctant to change unless we have a strong argument that some other way is better. This sounds very Bayesian, with a prior reducing the impact of new data. I agree completely, and I think Radford will very much enjoy my article with Aleks Jakulin , “Bayes: radical, liberal, or conservative?” Radford’s comment also fits with my increasing inclination to use informative prior distributions.
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