Types of probability distributions
In statistics, a symmetric probability distribution is a probability distribution—an assignment of probabilities to possible occurrences—which is unchanged when its probability density function (for continuous probability distribution) or probability mass function (for discrete random variables) is reflected around a vertical line at some value of the random variable represented by the distribution. This vertical line is the line of symmetry of the distribution. Thus the probability of being any given distance on one side of the value about which symmetry occurs is the same as the probability of being the same distance on the other side of that value. (Wikipedia).
Uniform Probability Distribution Examples
Overview and definition of a uniform probability distribution. Worked examples of how to find probabilities.
From playlist Probability Distributions
UNIFORM Probability Distribution for Discrete Random Variables (9-5)
Uniform Probability Distribution: (i.e., a rectangular distribution) is a probability distribution involving one random variable with a constant probability. Each potential outcome is equally likely, such as flipping coin and getting heads is always 50/50. On Chaos Night, Dante experiment
From playlist Discrete Probability Distributions in Statistics (WK 9 - QBA 237)
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
Distribution, Mean, Median, Mode, Range and Standard Deviation Lesson
This is part 1 of a lesson on describing data.
From playlist The Normal Distribution
Identifying, symmetric, skewed, uniform, and bell-shaped distributions
From playlist Unit 1: Descriptive Statistics
Multivariate Gaussian distributions
Properties of the multivariate Gaussian probability distribution
From playlist cs273a
Probability: We define geometric random variables, and find the mean, variance, and moment generating function of such. The key tools are the geometric power series and its derivatives.
From playlist Probability
Binomial and geometric distributions | Probability and Statistics | NJ Wildberger
We review the basic setup so far of a random variable X on a probability space (S,P), taking on values x_1,x_2,...,x_n with probabilities p_1,p_2,...,p_n. The associated probability distribution is just the record of the various values x_i and their probabilities p_i. It is this probabili
From playlist Probability and Statistics: an introduction
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Free ebook http://tinyurl.com/EngMathYT A basic introduction to symmetric matrices and their properties, including eigenvalues and eigenvectors. Several examples are presented to illustrate the ideas. Symmetric matrices enjoy interesting applications to quadratic forms.
From playlist Engineering Mathematics
Closer Look at RarerProbability - Wolfram Livecoding Session
Andreas Lauschke, a senior mathematical programmer, live-demos key Wolfram Language features useful in data science. In this eighth session, the built-in function RarerProbability is explored in more detail. Several general characteristics of continuous distributions are studied with Rarer
From playlist Data Science with Andreas Lauschke
Leonid Petrov (Virginia) -- Random polymers and symmetric functions
I will survey integrable random polymers (based on gamma / inverse gamma or beta distributed weights), and explain their connection to symmetric functions (respectively, gl_n Whittaker and new spin Whittaker functions). The work on spin Whittaker functions is joint with Matteo Mucciconi.
From playlist Integrable Probability Working Group
Algebraic Statistics of Random Integral Matrices by Hoi H. Nguyen
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From playlist TOPICS IN HIGH DIMENSIONAL PROBABILITY
Daniel Yekutieli: Hierarchical Bayes Modeling for Large-Scale Inference
CIRM VIRTUAL EVENT Recorded during the meeting "Mathematical Methods of Modern Statistics 2" the June 03, 2020 by the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by worldwide mathematicians
From playlist Virtual Conference
Markov processes and applications-5 by Hugo Touchette
PROGRAM : BANGALORE SCHOOL ON STATISTICAL PHYSICS - XII (ONLINE) ORGANIZERS : Abhishek Dhar (ICTS-TIFR, Bengaluru) and Sanjib Sabhapandit (RRI, Bengaluru) DATE : 28 June 2021 to 09 July 2021 VENUE : Online Due to the ongoing COVID-19 pandemic, the school will be conducted through online
From playlist Bangalore School on Statistical Physics - XII (ONLINE) 2021
Variational formulae for the capacity induced elliptic differential operators – C. Landim – ICM2018
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Entropy production and linear response in active Brownian particles by Debasish Chaudhuri
Stochastic Thermodynamics, Active Matter and Driven Systems DATE: 07 August 2017 to 11 August 2017 VENUE: Ramanujan Lecture Hall, ICTS Bangalore. Stochastic Thermodynamics and Active Systems are areas in statistical physics which have recently attracted a lot of attention and many intere
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From playlist Mathematics
Prob & Stats - Random Variable & Prob Distribution (42 of 53) Non-Symmetric Binomial Dist.
Visit http://ilectureonline.com for more math and science lectures! In this video I will graph a non-symmetric binomial distribution. Next video in series: http://youtu.be/0FIKgUwezxE
From playlist iLecturesOnline: Probability & Stats 2: Random Variable & Probability Distribution
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
On the Ising perceptron model - Nike Sun
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From playlist Mathematics