Digital Uplift Showcase: Business
This is a showcase of a historically difficult business course ACTL2131 - Probability and Mathematical Statistics which has been improved through the Digital Uplift process.
From playlist Digital Uplift Showcase
Statistics 5_1 Confidence Intervals
In this lecture explain the meaning of a confidence interval and look at the equation to calculate it.
From playlist Medical Statistics
What are "moments" in statistics? An intuitive video!
See the whole descriptive statistics playlist here: https://www.youtube.com/watch?v=bfQLNyiDPsk&list=PLTNMv857s9WVStKLco6ZBOsfSGXzJ1L0f See all my videos at http://www.zstatistics.com/videos/ 0:00 Introduction 1:23 Intuition behind moments 9:23 Higher order moments 12:10 Sampling adjustm
From playlist Descriptive Statistics (13 videos)
Francesco Mezzadri: Moments of Random Matrices and Hypergeometric Orthogonal Polynomials
We establish a new connection between moments of n×n random matrices $X_{n}$ and hypergeometric orthogonal polynomials. Specifically, we consider moments $\mathbb{E}\mathrm{Tr} X_n^{-s}$ as a function of the complex variable $s\in\mathbb{C}$, whose analytic structure we describe completely
From playlist Jean-Morlet Chair - Grava/Bufetov
This is an old video. See StatsMrR.com for access to hundreds of 1-3 minute, well-produced videos for learning Statistics. In this older video: Proportions are analyzed from a few perspectives, allowing us to more easily solve word problems and more easily set up proportions. Thinking o
From playlist Older Statistics Videos and Other Math Videos
The Most Powerful Tool Based Entirely On Randomness
We see the effects of randomness all around us on a day to day basis. In this video we’ll be discussing a couple of different techniques that scientists use to understand randomness, as well as how we can harness its power. Basically, we'll study the mathematics of randomness. The branch
From playlist Classical Physics by Parth G
This video explains how to determine mean, median and mode. It also provided examples. http://mathispower4u.yolasite.com/
From playlist Statistics: Describing Data
Statistics - How to use Chebyshev's Theorem
In this video I cover at little bit of what Chebyshev's theorem says, and how to use it. Remember that Chebyshev's theorem can be used with any distribution, and that it gives a lower proportion of what we can expect in the actual data. ▬▬ Chapters ▬▬▬▬▬▬▬▬▬▬▬ 0:00 Start 0:04 What is C
From playlist Statistics
Extreme Value Statistics: distribution of maxim
From playlist Extreme Value Statistics
Algebraic methods for point estimation
From playlist Fall 2018 Symbolic-Numeric Computing
Fellow Short Talks: Professor David Firth, University of Warwick
Bio Professor of Statistics at Warwick and Director of WDSI. Previously Professor of Social Statistics at Oxford. ESRC Professorial Fellow (2003-2006). Fellow of the British Academy (2008). RSS Guy Medals in Bronze (1998) and Silver (2012). John M Chambers Statistical Software Award, 2007
From playlist Short Talks
On convergence of numerical schemes for hyperbolic systems of conservation – S. Mishra – ICM2018
Numerical Analysis and Scientific Computing Invited Lecture 15.9 On the convergence of numerical schemes for hyperbolic systems of conservation laws Siddhartha Mishra Abstract: A large variety of efficient numerical methods, of the finite volume, finite difference and DG type, have been
From playlist Numerical Analysis and Scientific Computing
Efficiently Learning Mixtures of Gaussians - Ankur Moitra
Efficiently Learning Mixtures of Gaussians Ankur Moitra Massachusetts Institute of Technology January 18, 2011 Given data drawn from a mixture of multivariate Gaussians, a basic problem is to accurately estimate the mixture parameters. We provide a polynomial-time algorithm for this proble
From playlist Mathematics
The Power of Sampling by Peter W. Glynn
Infosys-ICTS Turing Lectures The Power of Sampling Speaker: Peter W. Glynn (Stanford University, USA) Date: 14 August 2019, 16:00 to 17:00 Venue: Ramanujan Lecture Hall, ICTS Bangalore Sampling-based methods arise in many statistical, computational, and engineering settings. In engine
From playlist Infosys-ICTS Turing Lectures
Jean-Michel Zakoïan: Testing the existence of moments for GARCH-type processes
It is generally admitted that financial time series have heavy tailed marginal distributions. When time series models are fitted on such data, the non-existence of appropriate moments may invalidate standard statistical tools used for inference. Moreover, the existence of moments can be cr
From playlist Probability and Statistics
Agnès Desolneux - Maximum Entropy Distributions for Image Synthesis under Statistical Constraints
The question of texture synthesis in image processing is a very challenging problem that can be stated as followed: given an exemplar image, sample a new image that has the same statistical features (empirical mean, empirical covariance, filter responses, neural network responses, etc.). E
From playlist Journée statistique & informatique pour la science des données à Paris-Saclay 2021
Statistical inference for networks: Professor Gesine Reinert, University of Oxford
Professor Gesine Reinert, Oxford University Research interests Applied Probability, Computational Biology, and Statistics. In particular: Stein’s method, networks, word count statistics Have you heard about the phenomenon that everyone is six handshakes away from the President? The six d
From playlist Data science classes
David O. Siegmund: Change: Detection,Estimation, Segmentation
CIRM VIRTUAL EVENT Recorded during the meeting "Mathematical Methods of Modern Statistics 2" the June 08, 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
David O. Siegmund: Change: Detection,Estimation, Segmentation
CIRM VIRTUAL EVENT Recorded during the meeting "Mathematical Methods of Modern Statistics 2" the June 08, 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
Cumulative Distribution Function (1 of 3: Definition)
More resources available at www.misterwootube.com
From playlist Random Variables