Generalized beta distribution

Continuous Distributions: Beta and Dirichlet Distributions

Video Lecture from the course INST 414: Advanced Data Science at UMD's iSchool. Full course information here: http://www.umiacs.umd.edu/~jbg/teaching/INST_414/

From playlist Advanced Data Science

Excel Beta Distribution (BETA.DIST)

How to use the BETA.DIST function in Excel for beta distribution cumulative probabilities. Three ways to format the function/

From playlist Excel for Statistics

(ML 7.5) Beta-Bernoulli model (part 1)

The Beta distribution is a conjugate prior for the Bernoulli. We derive the posterior distribution and the (posterior) predictive distribution under this model.

From playlist Machine Learning

(ML 7.6) Beta-Bernoulli model (part 2)

The Beta distribution is a conjugate prior for the Bernoulli. We derive the posterior distribution and the (posterior) predictive distribution under this model.

From playlist Machine Learning

Uniform Probability Distribution Examples

Overview and definition of a uniform probability distribution. Worked examples of how to find probabilities.

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

The Normal Distribution (1 of 3: Introductory definition)

More resources available at www.misterwootube.com

From playlist The Normal Distribution

Distribution, Mean, Median, Mode, Range and Standard Deviation Lesson

This is part 1 of a lesson on describing data.

From playlist The Normal Distribution

Zakhar Kabluchko: Random Polytopes II

In these three lectures we will provide an introduction to the subject of beta polytopes. These are random polytopes defined as convex hulls of i.i.d. samples from the beta density proportional to (1 − ∥x∥2)β on the d-dimensional unit ball. Similarly, beta’ polytopes are defined as convex

From playlist Workshop: High dimensional spatial random systems

Generalized Linear Model (Part B)

Regression Analysis by Dr. Soumen Maity,Department of Mathematics,IIT Kharagpur.For more details on NPTEL visit http://nptel.ac.in

From playlist IIT Kharagpur: Regression Analysis | CosmoLearning.org Mathematics

Using normal distribution to find the probability

👉 Learn how to find probability from a normal distribution curve. A set of data are said to be normally distributed if the set of data is symmetrical about the mean. The shape of a normal distribution curve is bell-shaped. The normal distribution curve is such that the mean is at the cente

From playlist Statistics

Discrepancy of generalized polynomials by Anirban Mukhopadhyay

Program Workshop on Additive Combinatorics ORGANIZERS: S. D. Adhikari and D. S. Ramana DATE: 24 February 2020 to 06 March 2020 VENUE: Madhava Lecture Hall, ICTS Bangalore Additive combinatorics is an active branch of mathematics that interfaces with combinatorics, number theory, ergod

From playlist Workshop on Additive Combinatorics 2020

Generalized Linear Model (Part A)

Regression Analysis by Dr. Soumen Maity,Department of Mathematics,IIT Kharagpur.For more details on NPTEL visit http://nptel.ac.in

From playlist IIT Kharagpur: Regression Analysis | CosmoLearning.org Mathematics

Some inter-relations between random matrix ensembles - Peter Forrester

Peter Forrester University of Melbourne October 16, 2013 In the early 1960's Dyson and Mehta found that the CSE relates to the COE. I'll discuss generalizations as well as other settings in random matrix theory in which β relates to 4/β. For more videos, visit http://video.ias.edu

From playlist Mathematics

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

Lecture 3 | Modern Physics: Statistical Mechanics

April 13, 2009 - Leonard Susskind reviews the Lagrange multiplier, explains Boltzmann distribution and Helm-Holtz free energy before oulining into the theory of fluctuations. Stanford University: http://www.stanford.edu/ Stanford Continuing Studies Program: http://csp.stanford.edu/

From playlist Lecture Collection | Modern Physics: Statistical Mechanics

Probability & Statistics in Finance

Mathematica 8 provides a suite of high-level functions for probability and statistics. New capabilities include the ability to compute the probability of any event or the expectation of any expression, simulate any distribution, and automatically estimate parameters or test goodness of fit

From playlist Wolfram Technology Conference 2010

Multivariate Gaussian distributions

Properties of the multivariate Gaussian probability distribution

From playlist cs273a

15. Regression (cont.)

MIT 18.650 Statistics for Applications, Fall 2016 View the complete course: http://ocw.mit.edu/18-650F16 Instructor: Philippe Rigollet In this lecture, Prof. Rigollet talked about significance test and other tests. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu

From playlist MIT 18.650 Statistics for Applications, Fall 2016