Probability Distribution Functions and Cumulative Distribution Functions
In this video we discuss the concept of probability distributions. These commonly take one of two forms, either the probability distribution function, f(x), or the cumulative distribution function, F(x). We examine both discrete and continuous versions of both functions and illustrate th
From playlist Probability
Cumulative Distribution Functions and Probability Density Functions
This statistics video tutorial provides a basic introduction into cumulative distribution functions and probability density functions. The probability density function or pdf is f(x) which describes the shape of the distribution. It can tell you if you have a uniform, exponential, or nor
From playlist Statistics
Probability Density Function of the Normal Distribution
More resources available at www.misterwootube.com
From playlist Random Variables
Ch9Pr18: Probability Distributions
A gentle introduction to probability distributions by looking at the uniform, binomial, geometric and Poisson distributions. This is Chapter 9 Problem 18 from the MATH1231/1241 Algebra notes. Presented by Thomas Britz from UNSW.
From playlist Mathematics 1B (Algebra)
What is a Sampling Distribution?
Intro to sampling distributions. What is a sampling distribution? What is the mean of the sampling distribution of the mean? Check out my e-book, Sampling in Statistics, which covers everything you need to know to find samples with more than 20 different techniques: https://prof-essa.creat
From playlist Probability Distributions
(PP 3.4) Random Variables with Densities
(0:00) Probability density function (PDF). (3:20) Indicator functions. (5:00) Examples of random variables with densities: Uniform, Exponential, Beta, Normal/Gaussian. A playlist of the Probability Primer series is available here: http://www.youtube.com/view_play_list?p=17567A1A3F5
From playlist Probability Theory
Uniform Probability Distribution Examples
Overview and definition of a uniform probability distribution. Worked examples of how to find probabilities.
From playlist Probability Distributions
05-1 Inverse modeling: deterministic inversion
Overview of deterministic inversion
From playlist QUSS GS 260
Physics inspired algorithms by Nisheeth Vishnoi
DISCUSSION MEETING : STATISTICAL PHYSICS OF MACHINE LEARNING ORGANIZERS : Chandan Dasgupta, Abhishek Dhar and Satya Majumdar DATE : 06 January 2020 to 10 January 2020 VENUE : Madhava Lecture Hall, ICTS Bangalore Machine learning techniques, especially “deep learning” using multilayer n
From playlist Statistical Physics of Machine Learning 2020
Top Eigenvalue of a Random Matrix: A tale of tails - Satya Majumdar
Speaker : Satya Majumdar (Directeur de Recherche in CNRS) Date and Time : 27 Jan 2012, 04:00 PM Venue : New Physical Sciences Building Auditorium, IISc, Bangalore Random matrices were first introduced by Wishart (1928) in the statistics literature to describe the covariance matrix of la
From playlist Top Eigenvalue of a Random Matrix: A tale of tails - Satya Majumdar
Frank Noé: "Connection between Statistics and Machine Learning"
Machine Learning for Physics and the Physics of Learning Tutorials 2019 "Connection between Statistics and Machine Learning" Frank Noé, Freie Universität Berlin Institute for Pure and Applied Mathematics, UCLA September 10, 2019 For more information: http://www.ipam.ucla.edu/programs/wo
From playlist Machine Learning for Physics and the Physics of Learning 2019
Extremal statistics in 1d Coulomb gas by Anupam Kundu
Large deviation theory in statistical physics: Recent advances and future challenges DATE: 14 August 2017 to 13 October 2017 VENUE: Madhava Lecture Hall, ICTS, Bengaluru Large deviation theory made its way into statistical physics as a mathematical framework for studying equilibrium syst
From playlist Large deviation theory in statistical physics: Recent advances and future challenges
Large deviations of Markov processes (Part - 1) by Hugo Touchette
Large deviation theory in statistical physics: Recent advances and future challenges DATE: 14 August 2017 to 13 October 2017 VENUE: Madhava Lecture Hall, ICTS, Bengaluru Large deviation theory made its way into statistical physics as a mathematical framework for studying equilibrium syst
From playlist Large deviation theory in statistical physics: Recent advances and future challenges
Random Matrices in Unexpected Places: Atomic Nuclei, Chaotic Billiards, Riemann Zeta #SoME2
Chapters: 0:00 Intro 2:21 What is RMT 7:12 Ensemble Averaging/Quantities of Interest 13:30 Gaussian Ensemble 18:03 Eigenvalues Repel 28:08 Recap 29:08 Three Surprising Coincidences 32:44 Billiards/Quantum Systems 36:00 Reimann Zeta ~~~~~~~~~~~~~~~~~~~~~~~~~ Errata + Clarifications ~~~~
From playlist Summer of Math Exposition 2 videos
Infinite-density versus large deviations theory for fat-tailed systems by Erez Aghion
Large deviation theory in statistical physics: Recent advances and future challenges DATE: 14 August 2017 to 13 October 2017 VENUE: Madhava Lecture Hall, ICTS, Bengaluru Large deviation theory made its way into statistical physics as a mathematical framework for studying equilibrium syst
From playlist Large deviation theory in statistical physics: Recent advances and future challenges
An overview and introduction to understanding sampling distributions of proportions [sample proportions] and how to calculate them
From playlist Unit 7 Probability C: Sampling Distributions & Simulation
Extreme statistics in 1d Coulomb gas by Anupam Kundu
Indian Statistical Physics Community Meeting 2018 DATE:16 February 2018 to 18 February 2018 VENUE:Ramanujan Lecture Hall, ICTS Bangalore This is an annual discussion meeting of the Indian statistical physics community which is attended by scientists, postdoctoral fellows, and graduate s
From playlist Indian Statistical Physics Community Meeting 2018
A First-Order Dynamical Transition in the displacement distribution by Satya N Majumdar
DISCUSSION MEETING INDIAN STATISTICAL PHYSICS COMMUNITY MEETING ORGANIZERS Ranjini Bandyopadhyay, Abhishek Dhar, Kavita Jain, Rahul Pandit, Sanjib Sabhapandit, Samriddhi Sankar Ray and Prerna Sharma DATE: 14 February 2019 to 16 February 2019 VENUE: Ramanujan Lecture Hall, ICTS Bangalo
From playlist Indian Statistical Physics Community Meeting 2019
Determining values of a variable at a particular percentile in a normal distribution
From playlist Unit 2: Normal Distributions