In probability a quasi-stationary distribution is a random process that admits one or several absorbing states that are reached almost surely, but is initially distributed such that it can evolve for a long time without reaching it. The most common example is the evolution of a population: the only equilibrium is when there is no one left, but if we model the number of people it is likely to remain stable for a long period of time before it eventually collapses. (Wikipedia).
Uniform Probability Distribution Examples
Overview and definition of a uniform probability distribution. Worked examples of how to find probabilities.
From playlist Probability Distributions
The Normal Distribution (1 of 3: Introductory definition)
More resources available at www.misterwootube.com
From playlist The Normal Distribution
Intro to non normal distributions. Several examples including exponential and Weibull.
From playlist Probability Distributions
Statistics: Introduction to the Shape of a Distribution of a Variable
This video introduces some of the more common shapes of distributions http://mathispower4u.com
From playlist Statistics: Describing Data
OCR MEI Statistics 2 2.01 Introducing the Poisson Distribution
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From playlist [OLD SPEC] TEACHING OCR MEI STATISTICS 2 (S2)
Continuous Probability Distributions - Basic Introduction
This statistics video tutorial provides a basic introduction into continuous probability distributions. It discusses the normal distribution, uniform distribution, and the exponential distribution. The probability is equal to the area under the curve and the total area under the curve is
From playlist Statistics
Some questions around quasi-periodic dynamics – Bassam Fayad & Raphaël Krikorian – ICM2018
Dynamical Systems and Ordinary Differential Equations Invited Lecture 9.2 Some questions around quasi-periodic dynamics Bassam Fayad & Raphaël Krikorian Abstract: We propose in these notes a list of some old and new questions related to quasi-periodic dynamics. A main aspect of quasi-per
From playlist Dynamical Systems and ODE
Nonequilibrium Extension of the Third Law of Thermodynamics by Christian Maes
DISCUSSION MEETING : STATISTICAL PHYSICS OF COMPLEX SYSTEMS ORGANIZERS : Sumedha (NISER, India), Abhishek Dhar (ICTS-TIFR, India), Satya Majumdar (University of Paris-Saclay, France), R Rajesh (IMSc, India), Sanjib Sabhapandit (RRI, India) and Tridib Sadhu (TIFR, India) DATE : 19 December
From playlist Statistical Physics of Complex Systems - 2022
The Continuous Uniform Distribution
From playlist Probability Distributions
A disordered open long-range exclusion process by Arvind Ayyer
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
Quasi-static hydrodynamic limits by Stefano Olla
DISCUSSION MEETING : HYDRODYNAMICS AND FLUCTUATIONS - MICROSCOPIC APPROACHES IN CONDENSED MATTER SYSTEMS (ONLINE) ORGANIZERS : Abhishek Dhar (ICTS-TIFR, India), Keiji Saito (Keio University, Japan) and Tomohiro Sasamoto (Tokyo Institute of Technology, Japan) DATE : 06 September 2021 to 1
From playlist Hydrodynamics and fluctuations - microscopic approaches in condensed matter systems (ONLINE) 2021
Non-unique Steady States in Birth Death Diffusion Processes by Pradeep K Mohanty
DISCUSSION MEETING STATISTICAL PHYSICS: RECENT ADVANCES AND FUTURE DIRECTIONS (ONLINE) ORGANIZERS: Sakuntala Chatterjee (SNBNCBS, Kolkata), Kavita Jain (JNCASR, Bangalore) and Tridib Sadhu (TIFR, Mumbai) DATE: 14 February 2022 to 15 February 2022 VENUE: Online In the past few decades,
From playlist Statistical Physics: Recent advances and Future directions (ONLINE) 2022
Courses - G. JONA LASINIO “Macroscopic Fluctuation Theory”
Stationary non-equilibrium states describe steady flows through macroscopic systems. Although they represent the simplest generalization of equilibrium states, they exhibit a variety of new phenomena. Within a statistical mechanics approach, these states have been the subject of several th
From playlist T1-2015 : Disordered systems, random spatial processes and some applications
Colloquium MathAlp 2018 - Christian Gérard
Aspects de la théorie quantique des champs en espace-temps courbe La théorie quantique des champs est formulée d'habitude sur l'espace-temps plat de Minkowski. L'extension de ce cadre à des espaces-temps généraux permet de mettre en lumière de nouveaux phénomènes quantiques qui surviennen
From playlist Colloquiums MathAlp
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
[T1 2022] Coralie Fritsch - Quasi-stationary behavior for the Crump-Young model of chemostat
Joint work with Bertrand Cloez. The Crump-Young model consists of two fully coupled stochastic processes modeling the substrate and micro-organisms dynamics in a chemostat. The substrate evolves follo-wing an ordinary di˙erential equation, depending on the micro-organisms number. Micro-or
From playlist [T1 2022] Workshop - Mathematical models in ecology and evolution - March 21st to 25th, 2022
Anomalous spin diffusion in one-dimensional antiferromagnets by Jacopo De Nardis
PROGRAM THERMALIZATION, MANY BODY LOCALIZATION AND HYDRODYNAMICS ORGANIZERS: Dmitry Abanin, Abhishek Dhar, François Huveneers, Takahiro Sagawa, Keiji Saito, Herbert Spohn and Hal Tasaki DATE : 11 November 2019 to 29 November 2019 VENUE: Ramanujan Lecture Hall, ICTS Bangalore How do is
From playlist Thermalization, Many Body Localization And Hydrodynamics 2019
This is the first lecture on "A Markovian perspective on some singular SPDEs" taught by Professor Nicolas Perkowski. For more materials and slides visit: https://sites.google.com/view/oneworld-pderandom/home
From playlist Summer School on PDE & Randomness
Tutorial: Time Series Analysis - Matthew Graham - 6/24/2019
AstroInformatics 2019 Conference: Data Science and X-informatics http://astroinformatics2019.org/
From playlist AstroInformatics 2019 Conference