Archives


Towards thearetical understanding of deep learning by Sanjeev Arora [outside article]

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A presentation on Deep Learning including a brief history and tutorial. https://www.dropbox.com/s/qonozmne0x4x2r3/deepsurveyICML18final.pptx

Which test to use in what situation [outside article]

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Having trouble deciding what statistical test to use for your data? Use this handy flowchart from Penn State to decide. It includes a review of all the statistical techniques provided, as well as a table consisting of inferences, parameters, statistics, types of data, examples, analysis, Minitab commands, and conditions.     https://newonlinecourses.science.psu.edu/stat500/node/67/

American Statistical Association’s statement on p-values [outside article]

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The American Statistical Association (ASA) has released a “Statement on Statistical Significance and P-Values” with six principles underlying the proper use and interpretation of the p-value. The ASA releases this guidance on p-values to improve the conduct and interpretation of quantitative science and inform the growing emphasis on reproducibility of science research. The statement also… Read More

Why Frank Harrell does not like p-values by Frank Harrel [outside article]

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With the many problems that p-values have, and the temptation to “bless” research when the p-value falls below an arbitrary threshold such as 0.05 or 0.005, researchers using p-values should at least be fully aware of what they are getting. They need to know exactly what a p-value means and what are the assumptions required… Read More

Note on small p-value hacking by Thomas Lumley [outside article]

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The proposal to change p-value thresholds from 0.05 to 0.005 won’t die. I think it’s targeting the wrong question:  many studies are too weak in various ways to provide the sort of reliable evidence they want to claim, and the choices available in analysis and publication process eat up too much of that limited information. … Read More