Statistics | Probability distributions
The Kaniadakis Weibull distribution (or κ-Weibull distribution) is a probability distribution arising as a generalization of the Weibull distribution. It is one example of a Kaniadakis κ-distribution. The κ-Weibull distribution has been adopted successfully for describing a wide variety of complex systems in seismology, economy, epidemiology, among many others. (Wikipedia).
Frobenius distribution for pairs of elliptic curves and exceptional isogenies - Francois Charles
Francois Charles March 13, 2015 Workshop on Chow groups, motives and derived categories More videos on http://video.ias.edu
From playlist Mathematics
Value distribution of long Dirichlet polynomials and applications to the Riemann...-Maksym Radziwill
Maksym Radziwill Value distribution of long Dirichlet polynomials and applications to the Riemann zeta-function Stanford University; Member, School of Mathematics October 1, 2013 For more videos, visit http://video.ias.edu
From playlist Mathematics
(ML 7.7.A1) Dirichlet distribution
Definition of the Dirichlet distribution, what it looks like, intuition for what the parameters control, and some statistics: mean, mode, and variance.
From playlist Machine Learning
What is a Unimodal Distribution?
Quick definition of a unimodal distribution and how it compares to a bimodal distribution and a multimodal distribution.
From playlist Probability Distributions
Weibull modulus and probabilistic design
0:00 variation in data, histograms of data, average values, standard deviation 9:00 normal distribution, six sigma 10:31 safety factors in engineering design 13:47 the 2-parameter Weibull equation 16:40 defining failure probability, F 18:40 excel example of calculating Weibull modulus 27:
From playlist Introduction to Materials Science and Engineering Fall 2018
Advice for Maths Exploration | Chebyshev and Spread Polynumbers: the remarkable Goh factorization
A key challenge for amateur mathematicians is finding a fruitful and accessible and interesting area for investigation. This is not so easy: classical number theory is certainly very interesting but it is highly difficult, perhaps even unrealistic, to hope to make really new discoveries he
From playlist Maxel inverses and orthogonal polynomials (non-Members)
Mod-17 Lec-45 Mechanical Properties of Ceramic Materials ( Contd.)
Advanced ceramics for strategic applications by Prof. H.S. Maiti,Department of Metallurgy and Material Science,IIT Kharagpur.For more details on NPTEL visit http://nptel.ac.in
From playlist IIT Kharagpur: Advanced Ceramics for Strategic Applications | CosmoLearning.org Materials Science
10/26/2016 Intro to MSE weibull statistics and probabilistic design
Callister Intro to MSE, materials science, Weibull statistics, fracture, failure, probabilistic design, safety factor, standard deviation, variability, six sigma, data extrapolation, failure example, weibull calculation, weibull modulus, characteristic strength, effective area, design of
From playlist Introduction to Materials Science and Engineering Fall 2016
Advice for prospective research mathematicians | Rational Trigonometry and spread polynomials 1
Here is a quick introduction / review of the essentials of Rational Trigonometry, with an aim to explaining the important spread polynomials / polynumbers which are more pleasant variants of the Chebyshev polynomials of the first kind. Our treatment here is quite concise, relying on a pri
From playlist Maxel inverses and orthogonal polynomials (non-Members)
Day 22 Weibull modulus and Probabilistic design
0:00 reading quiz 5:43 polymer creep 6:42 hardness 9:24 variability in data demo 15:00 average values vs standard deviation vs 6sigma 19:54 safety factor and design factor vs probabilistic design 21:40 Weibull modulus 25:25 steps for weibull analysis 30:45 using Weibull analysis to design
From playlist Introduction to Materials Science and Engineering Fall 2017
Introduction to Weibull Modulus and predictive failure analysis
ariability in data standard deviations the weibull equation worked example for strength at specific failure rate scaling from test bars to components using effective area ratios
From playlist Introduction to Materials Science & Engineering Fall 2019
Weibull modulus and probabilistic design example problem
Using Weibull analysis to do probabilistic failure design. Determining what stress will yield an arbitrarily defined survival or failure rate. Effective area scaling to determine what stress will cause equal failure rates of test bars vs actual components.
From playlist MSE example problems tutorial
Advice for Research Mathematicians | Rational Trigonometry and Spread Polynomials II | Wild Egg Math
Spread polynomials arise in Rational Trigonometry as variants of the Chebyshev polynomials of the first kind. However the spread polynomials arise in a purely algebraic setting, without any need for appeal to "transcendental functions" which can't actually be evaluated -- such as cos x or
From playlist Maxel inverses and orthogonal polynomials (non-Members)
Learn more about programming in MATLAB and how to be more productive with MATLAB. Get a Free MATLAB Trial: https://goo.gl/C2Y9A5 Ready to Buy: https://goo.gl/vsIeA5 Learn more about MATLAB: http://goo.gl/YKadxi MATLAB is a high-level language that includes mathematical functions for so
From playlist MATLAB Virtual Conference 2013
Bernoulli Distribution In Statistics | Bernoulli Distribution Problems and Solutions | Simplilearn
In this Bernoulli Distribution In Statistics tutorial, we will learn Bernoulli distribution and its use. We will also solve a problem related to Bernoulli distribution. In the end, we will see some real-life examples where Bernoulli distribution is used, and we will execute Bernoulli distr
(ML 7.9) Posterior distribution for univariate Gaussian (part 1)
Computing the posterior distribution for the mean of the univariate Gaussian, with a Gaussian prior (assuming known prior mean, and known variances). The posterior is Gaussian, showing that the Gaussian is a conjugate prior for the mean of a Gaussian.
From playlist Machine Learning
We continue the search for the mathematics most supportive of prediction within geology. We explore mineralizing systems and find giant ore deposits. We search for black swans and dragon kings and find generalized gamma and extreme value distributions. Power-law and log-normal distribution
From playlist Wolfram Technology Conference 2021
(ML 7.10) Posterior distribution for univariate Gaussian (part 2)
Computing the posterior distribution for the mean of the univariate Gaussian, with a Gaussian prior (assuming known prior mean, and known variances). The posterior is Gaussian, showing that the Gaussian is a conjugate prior for the mean of a Gaussian.
From playlist Machine Learning
Tutorial for determining Weibull modulus in excel
short 6 minute step by step tutorial for using excel to determine weibull modulus for test data.
From playlist Software tutorials