statistics – Page 7 – Andrew Fairless, Ph.D.

What I Read: Machine learning is not nonparametric statistics

By Andrew Fairless on October 20, 2021October 16, 2021

https://www.argmin.net/2021/10/13/prediction/ Machine learning is not nonparametric statistics.Ben RechtOct 13, 2021 “…I’ve been told by respected statisticians that machine learning is nothing more than nonparametric statistics. The longer I work inContinue readingWhat I Read: Machine learning is not nonparametric statistics

What I Read: Bayesian Media Mix Modeling

By Andrew Fairless on October 7, 2021September 21, 2021

Bayesian Media Mix Modeling for Marketing OptimizationBenjamin Vincent2021-09-17 “Fortunately, with Bayesian modeling, we can do better than this! So-called Media Mix Modelling (MMM) can estimate how effective each advertising channelContinue readingWhat I Read: Bayesian Media Mix Modeling

What I Read: Dissecting “Noise”

By Andrew Fairless on September 21, 2021September 4, 2021

https://www.lareviewofbooks.org/article/dissecting-noise/ Dissecting “Noise”By Vasant DharAUGUST 9, 2021 “WHAT IS NOISE? If two felons receive sentences of three years and seven years when they should both be sentenced to five, theContinue readingWhat I Read: Dissecting “Noise”

What I Read: Pathfinder, A parallel quasi-Newton algorithm

By Andrew Fairless on September 2, 2021August 17, 2021

https://statmodeling.stat.columbia.edu/2021/08/10/pathfinder-a-parallel-quasi-newton-algorithm-for-reaching-regions-of-high-probability-mass/ Pathfinder: A parallel quasi-Newton algorithm for reaching regions of high probability massAndrew Gelman10 August 2021, 9:07 am “In the world of Stan, we see three roles for Pathfinder: (1)Continue readingWhat I Read: Pathfinder, A parallel quasi-Newton algorithm

What I Read: Why Deep Learning Works

By Andrew Fairless on August 23, 2021August 17, 2021

https://moultano.wordpress.com/2020/10/18/why-deep-learning-works-even-though-it-shouldnt/ Why Deep Learning Works Even Though It Shouldn’tRyan Moulton’s ArticlesRyan Moulton “Stop talking about minima…. Nobody ever trains their model remotely close to convergence…. What really needs further researchContinue readingWhat I Read: Why Deep Learning Works

What I Read: Causal Inference, Elasticity Pricing

By Andrew Fairless on July 23, 2021July 12, 2021

https://towardsdatascience.com/causal-inference-example-elasticity-de4a3e2e621b?gi=cb88b072c5b9 Causal Inference in the Wild: Elasticity PricingHow can machine learning to improve causal inference in industry? I describe a real example with code for retail pricing.Lars RoemheldJuly 8, 2021Continue readingWhat I Read: Causal Inference, Elasticity Pricing

What I Read: null hypothesis significance testing falls apart when considering replications

By Andrew Fairless on July 8, 2021June 22, 2021

https://statmodeling.stat.columbia.edu/2021/06/17/guttman-points-out-another-problem-with-null-hypothesis-significance-testing-it-falls-apart-when-considering-replications/ Guttman points out another problem with null hypothesis significance testing: It falls apart when considering replications.by Andrew Gelman17 June 2021, 9:22 am “… another problem with null hypothesis significanceContinue readingWhat I Read: null hypothesis significance testing falls apart when considering replications

What I Read: 3 Statistical Paradoxes

By Andrew Fairless on May 13, 2021April 17, 2021

https://towardsdatascience.com/top-3-statistical-paradoxes-in-data-science-e2dc37535d99 Top 3 Statistical Paradoxes in Data ScienceObservation bias and sub-group differences generate statistical paradoxes.Francesco Casalegno “Observation bias and sub-group differences can easily produce statistical paradoxes in any data scienceContinue readingWhat I Read: 3 Statistical Paradoxes

What I Read: Scaling vs. Normalizing Data

By Andrew Fairless on April 19, 2021April 2, 2021

https://towardsai.net/p/data-science/scaling-vs-normalizing-data-5c3514887a84 Data ScienceScaling vs. Normalizing DataJanuary 10, 2021Author(s): Lawrence Alaso Krukrubo “Scaling and normalization are so similar that they’re often applied interchangeably, but as we’ve seen from the definitions, theyContinue readingWhat I Read: Scaling vs. Normalizing Data

What I Read: Rip van Winkle’s Razor, Adaptive Data Analysis

By Andrew Fairless on April 17, 2021April 10, 2021

http://www.offconvex.org/2021/04/07/ripvanwinkle/ Rip van Winkle’s Razor, a Simple New Estimate for Adaptive Data AnalysisSanjeev Arora, Yi ZhangApr 7, 2021 “Can you trust a model whose designer had access to the test/holdoutContinue readingWhat I Read: Rip van Winkle’s Razor, Adaptive Data Analysis

Tag: statistics