statistics – Andrew Fairless, Ph.D.

What I Read: Data Missing

By Andrew Fairless on January 22, 2025October 19, 2024

https://www.quantamagazine.org/when-data-is-missing-scientists-guess-then-guess-again-20241002/ When Data Is Missing, Scientists Guess. Then Guess Again.Matt von HippelOctober 2, 2024 “Across the social and biological sciences, statisticians use a technique that leverages randomness to deal withContinue readingWhat I Read: Data Missing

What I Read: Jensen’s Inequality

By Andrew Fairless on January 15, 2025September 29, 2024

https://blog.moontower.ai/jensens-inequality-as-an-intuition-tool Jensen’s Inequality As An Intuition ToolKris AbdelmessihSep 29, 2021 “…Jensen’s Inequality informs us when an average occurance is a poor predictor of the average result.”

What I Read: Hampel Filter, time series

By Andrew Fairless on January 13, 2025September 29, 2024

https://medium.com/data-and-beyond/outlier-detection-in-r-hampel-filter-for-time-series-15ca7d166067 Outlier Detection in R: Hampel Filter for time seriesDima DiachkovFeb 2, 2024 “The Hampel Filter identifies outliers based on the median absolute deviation (MAD), a measure less affected byContinue readingWhat I Read: Hampel Filter, time series

What I Read: Sphering Transform

By Andrew Fairless on January 7, 2025September 29, 2024

Detecting Data Differences Using the Sphering Transform Detecting Data Differences Using the Sphering TransformBy Nina ZumelAugust 20, 2023 “Why do we want to sphere-transform our data? One reason is thatContinue readingWhat I Read: Sphering Transform

What I Read: Regularization, polynomial bases

By Andrew Fairless on November 7, 2024August 25, 2024

https://alexshtf.github.io/2024/06/03/PolynomialBasesRegProps.html Alex ShtoffRegularization properties of polynomial basesJun 3, 2024 “We used the Bernstein basis to demonstrate the importance of chosing a “good” polynomial basis, and that other well-known bases mayContinue readingWhat I Read: Regularization, polynomial bases

What I Read: Contextual Bandit, LinUCB:

By Andrew Fairless on November 5, 2024August 15, 2024

https://truetheta.io/concepts/reinforcement-learning/lin-ucb A Reliable Contextual Bandit Algorithm: LinUCBDJ RichAugust 6, 2024 “A user visits a news website. Which articles should they be shown?”

What I Read: standard error

By Andrew Fairless on October 22, 2024July 22, 2024

http://www.stat.columbia.edu/~gelman/research/published/standarderror.pdf What is a standard error?Andrew Gelman7 September 2023 “In statistics, the standard error has a clear technical definition… In practice, though, challenges arise when we go beyond the simpleContinue readingWhat I Read: standard error

What I Read: Use-cases, inverted PCA

By Andrew Fairless on October 16, 2024July 14, 2024

https://www.youtube.com/watch?v=ZK3_T-UgKWM Use-cases for inverted PCA:probabl.Jul 11, 2024 “A lot of people know of PCA for it’s ability to reduce the dimensionality of a dataset. It can turn a wide datasetContinue readingWhat I Read: Use-cases, inverted PCA

What I Read: decision analysis, significance testing

By Andrew Fairless on October 3, 2024July 14, 2024

https://statmodeling.stat.columbia.edu/2024/07/10/a-misunderstanding-about-decision-analysis-and-significance-testing (Trying to) clear up a misunderstanding about decision analysis and significance testingAndrew Gelman7/10/24 9:03 AM “…we’re just saying that screening based on statistical significance has lots of problems. P-valuesContinue readingWhat I Read: decision analysis, significance testing

What I Read: Logarithms, Heteroskedasticity

By Andrew Fairless on August 29, 2024June 15, 2024

https://allendowney.substack.com/p/logarithms-and-heteroskedasticity Logarithms and HeteroskedasticityAllen DowneyMay 26, 2024 “A log transform is neither necessary nor sufficient to fix heteroskedasticity”

Tag: statistics