# ARGUS distribution

In physics, the ARGUS distribution, named after the particle physics experiment ARGUS, is the probability distribution of the reconstructed invariant mass of a decayed particle candidate in continuum background. (Wikipedia).

The Normal Distribution (1 of 3: Introductory definition)

More resources available at www.misterwootube.com

From playlist The Normal Distribution

Excel 2013 Statistical Analysis #09: Cumulative Frequency Distribution & Chart, PivotTable & Formula

Download files: https://people.highline.edu/mgirvin/AllClasses/210Excel2013/Ch02/Excel2013StatisticsChapter02.xlsx Topics in this video: 1. (00:09) Overview of % Cumulative Frequency 2. (00:42) Formulas to create Cumulative Frequency Distribution and % Cumulative Frequency Distribution. 3.

Statistics Lecture 6.3: The Standard Normal Distribution. Using z-score, Standard Score

https://www.patreon.com/ProfessorLeonard Statistics Lecture 6.3: Applications of the Standard Normal Distribution. Using z-score, Standard Score

From playlist Statistics (Full Length Videos)

(English Version: https://www.youtube.com/watch?v=DosqbEy8ecY) http://www.nucleusinc.com/ - 这个三维动画介绍了右髋关节的全髋关节置换术。该手术包括切开、露出髋关节、放置髋臼修复假体（窝）、割掉发炎的股沟头、放置股骨头假体（球）。

From playlist 在中国医学动画

Mean of Grouped Frequency Tables

"Calculate mean from grouped frequency tables."

From playlist Data Handling: Frequency Tables

What is the t-distribution? An extensive guide!

See all my videos at http://www.zstatistics.com/videos/ 0:00 Introduction 2:17 Overview 6:06 Sampling RECAP 12:27 Visualising the t distribution 14:24 Calculating values from the t distribution (EXCEL and t-tables!)

From playlist Distributions (10 videos)

7 - MegaFavNumbers

#MegaFavNumbers

From playlist MegaFavNumbers

Inverse normal with Z Table

Determining values of a variable at a particular percentile in a normal distribution

From playlist Unit 2: Normal Distributions

Introduction to the Standard Normal Distribution

This video introduces the standard normal distribution http://mathispower4u.com

From playlist The Normal Distribution

A polynomial lower bound for monotonicity testing...- Rocco Servedio

Rocco Servedio Columbia University March 31, 2014 We prove a Ω̃ (n1/5)Ω~(n1/5) lower bound on the query complexity of any non-adaptive two-sided error algorithm for testing whether an unknown n-variable Boolean function is monotone versus constant-far from monotone. This gives an exponenti

From playlist Mathematics

Gaussian multiplicative chaos: applications and recent developments - Nina Holden

50 Years of Number Theory and Random Matrix Theory Conference Topic: Gaussian multiplicative chaos: applications and recent developments Speaker: Nina Holden Affiliation: ETH Zurich Date: June 22, 2022 I will give an introduction to Gaussian multiplicative chaos and some of its applicati

From playlist Mathematics

L22.8 The Fresh Start Property and Its Implications

MIT RES.6-012 Introduction to Probability, Spring 2018 View the complete course: https://ocw.mit.edu/RES-6-012S18 Instructor: John Tsitsiklis License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu

Mod-01 Lec-19 Ricardo-Malthus debate

History of Economic Theory by Dr. Shivakumar, Department of Humanities and Social Sciences IIT Madras, For more details on NPTEL visit http://nptel.iitm.ac.in

Is Google Translate Sexist? Gender Stereotypes in Statistical Machine Translation

#genderbias #algorithmicfairness #debiasing A brief look into gender stereotypes in Google Translate. The origin is a Tweet containing a Hungarian text. Hungarian is a gender-neutral language, so translating gender pronouns is ambiguous. Turns out that Google Translate assigns very stereo

From playlist ML in Society

Discriminating Systems - Gender, Race, and Power in AI

TL;DR: - There exists both an unequal representation of people in the AI workforce as well as examples of societal bias in AI systems. - The authors claim that the former causally leads to the latter and vice versa. - To me, the report does not manage to make a strong enough argument for t

From playlist ML in Society

AI DEBATE : Yoshua Bengio | Gary Marcus

Yoshua Bengio and Gary Marcus on the best way forward for AI Moderated by Vincent Boucher ORIGINAL LIVE STREAMING | Monday, 23 December 2019 from 6:30 PM to 8:30 PM (EST) at Mila: https://www.facebook.com/MontrealAI/videos/498403850881660/ Transcript of the AI Debate: https://medium.com/

From playlist AI talks

AQC 2016 - Quantum Monte Carlo vs Tunneling vs. Adiabatic Optimization

A Google TechTalk, June 27, 2016, presented by Aram Harrow (MIT) ABSTRACT: Can quantum adiabatic evolution solve optimization problems much faster than classical computers? One piece of evidence for this has been their apparent advantage in "tunneling" through barriers to escape local mi

From playlist Adiabatic Quantum Computing Conference 2016

Stochastic Mechanisms of Cell-Size Regulation in Bacteria by Anatoly Kolomeisky

PROGRAM STATISTICAL BIOLOGICAL PHYSICS: FROM SINGLE MOLECULE TO CELL (ONLINE) ORGANIZERS: Debashish Chowdhury (IIT Kanpur), Ambarish Kunwar (IIT Bombay) and Prabal K Maiti (IISc, Bengaluru) DATE: 07 December 2020 to 18 December 2020 VENUE: Online 'Fluctuation-and-noise' are themes tha

Ben Glocker: "Causality matters in medical imaging"

Deep Learning and Medical Applications 2020 "Causality matters in medical imaging" Ben Glocker - Imperial College London, Department of Computing Abstract: We use causal reasoning to shed new light on key challenges in medical imaging: 1) data scarcity, which is the limited availability

From playlist Deep Learning and Medical Applications 2020

(ML 7.7.A1) Dirichlet distribution

Definition of the Dirichlet distribution, what it looks like, intuition for what the parameters control, and some statistics: mean, mode, and variance.

From playlist Machine Learning

## Related pages

Gamma function | Consistent estimator | Bessel function | Real number | Probability distribution | Probability density function | Cumulative distribution function