Statistical paradoxes

Accuracy paradox

The accuracy paradox is the paradoxical finding that accuracy is not a good metric for predictive models when classifying in predictive analytics. This is because a simple model may have a high level of accuracy but be too crude to be useful. For example, if the incidence of category A is dominant, being found in 99% of cases, then predicting that every case is category A will have an accuracy of 99%. Precision and recall are better measures in such cases.The underlying issue is that there is a class imbalance between the positive class and the negative class. Prior probabilities for these classes need to be accounted for in error analysis. Precision and recall help, but precision too can be biased by very unbalanced class priors in the test sets. (Wikipedia).

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Accuracy and Precision

This chemistry video tutorial explains the difference of accuracy and precision in measurement. This video gives an example of four students attempting to measure the density of aluminum and asks which data is accurate but not precise. Accuracy has to do with how close your data is to th

From playlist New AP & General Chemistry Video Playlist

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What Are Error Intervals? GCSE Maths Revision

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From playlist Error Intervals & Bounds GCSE Maths Revision

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In this lecture explain the meaning of a confidence interval and look at the equation to calculate it.

From playlist Medical Statistics

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Teach Astronomy - Accuracy and Precision

http://www.teachastronomy.com/ Scientists try to make measurements of high accuracy. Accuracy means that the value that's measured through an observation is very close to the true value. It also means that if multiple measurements are made, we can increase the accuracy of a measurement.

From playlist 01. Fundamentals of Science and Astronomy

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Evaluation 8: F-measure

F-measure is a harmonic mean of recall and precision. Think of it as accuracy, but without the effect of true negatives (which made accuracy meaningless for evaluating search algorithms). F-measure can also be interpreted as the Dice coefficient between the relevant set and the retrieved s

From playlist IR13 Evaluating Search Engines

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The medical test paradox, and redesigning Bayes' rule

About Likelihood Ratios, also sometimes called Bayes Factors*. Help fund future projects: https://www.patreon.com/3blue1brown An equally valuable form of support is to simply share some of the videos. Special thanks to these supporters: https://3b1b.co/bayes-factor-thanks Home page: https:

From playlist Prob and Stats

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From playlist "Smarter In-A-Minute" Math on Shorts

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Fourteenth Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS Virtual Seminar Series Talk

Date: Wednesday, February 17, 2021, 10:00am EDT Speaker: Anders Hansen, University of Cambridge Title: On the foundations of computational mathematics, Smale’s 18th problem and the potential limits of AI Abstract: There is a profound optimism on the impact of deep learning (DL) and AI w

From playlist Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS Virtual Seminar Series

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Location Intelligence Products: Goals and Challenges | AISC

For slides and more information on the paper, visit https://aisc.ai.science/events/2019-10-15-ai-product Discussion lead: Arthur Berrill

From playlist AI Products

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Introduction to Accuracy and Precision (includes Relative Error)

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From playlist IB Physics 1: Measurements and Uncertainties

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The Information Paradox and State-Dependence by Suvrat Raju

21 November 2016 to 10 December 2016 VENUE Ramanujan Lecture Hall, ICTS Bangalore Quantum Theory has passed all experimental tests, with impressive accuracy. It applies to light and matter from the smallest scales so far explored, up to the mesoscopic scale. It is also a necessary ingredie

From playlist Fundamental Problems of Quantum Physics

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The Role of Theory in Science - David Gross

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From playlist Public Lectures

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Revisiting the black hole information paradox by Pushkal Shrivastava

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From playlist ICTS In-house 2020

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Ruby Conference 2007 Essential Incompleteness in Program Modeling by Luke Kanies

Help us caption & translate this video! http://amara.org/v/FGcs/

From playlist Ruby Conference 2007

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Should you trust unanimous decisions? - Derek Abbott

View full lesson: http://ed.ted.com/lessons/should-you-trust-unanimous-decisions-derek-abbott Imagine a police lineup where ten witnesses are asked to identify a bank robber they glimpsed fleeing the scene. If six of them pick the same person, there’s a good chance that’s the culprit. And

From playlist New TED-Ed Originals

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Vigyan Adda Talk: Black Holes and the Reversibility of Time by Suvrat Raju

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From playlist Vigyan Adda

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IntervalsForRegression.4.PredictionIntervals

This video is brought to you by the Quantitative Analysis Institute at Wellesley College. The material is best viewed as part of the online resources that organize the content and include questions for checking understanding: https://www.wellesley.edu/qai/onlineresources

From playlist Intervals for Regression

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Confusion matrix | Predictive analytics | Binary classification