Intro to non normal distributions. Several examples including exponential and Weibull.
From playlist Probability Distributions
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
Lecturer: Dr. Erin M. Buchanan Missouri State University Spring 2016 I am so excited to show you our new effect size scripts! You enter the basic statistics you have from your output, and these scripts will calculate your test statistic, p values, confidence interval for the mean, effect
From playlist Advanced Statistics Videos
Nonparametric additive regression β Byeong Park β ICM2018
Probability and Statistics Invited Lecture 12.4 Nonparametric additive regression Byeong Park Abstract: In this article we discuss statistical methods of estimating structured nonparametric regression models. Our discussion is mainly on the additive models where the regression function (
From playlist Probability and Statistics
The Normal Distribution (1 of 3: Introductory definition)
More resources available at www.misterwootube.com
From playlist The Normal Distribution
Positioned for Success: Targeting Mathematica to Strengthen U.S. Defense
When a contractor for the U.S. Department of Defense called on Bruce Colletti to develop a geo-positioning application for precision targeting, Colletti called on Mathematica. Mathematica is the only software available that he could use to combine the vast technical and programmatic functi
From playlist Wolfram Research: Portraits of Success
The Generalized Likelihood Ratio Test
http://AllSignalProcessing.com for more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files. There is no universally optimal test strategy for composite hypotheses (unknown parameters in the pdfs). The generalized likelihood ratio test (GLRT
From playlist Estimation and Detection Theory
R - MOTE Package Avaliable on GitHub
Lecturer: Dr. Erin M. Buchanan Missouri State University Summer 2017 You can check out our package on git: https://github.com/doomlab/MOTE You can install with this code: install.packages("devtools") ##only needed if you do not have it yet devtools::install_github("doomlab/MOTE")
From playlist Learn R + Statistics
19 - Beta distribution - an introduction
This video provides an introduction to the beta distribution; giving its definition, explaining why we may use it, and the range of beliefs that can be described by this versatile distribution. If you are interested in seeing more of the material, arranged into a playlist, please visit: h
From playlist Bayesian statistics: a comprehensive course
29 - Posterior predictive distribution: example Disease
This video provides an introduction to the concept of posterior predictive distributions, using the example of disease prevalence in a population. Here we consider the case of a beta prior and binomial likelihood; resulting in a beta-binomial posterior. If you are interested in seeing mo
From playlist Bayesian statistics: a comprehensive course
Find the probability of an event using a normal distribution curve
π 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
(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
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 β β₯xβ₯2)Ξ² on the d-dimensional unit ball. Similarly, betaβ 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
39 - The gamma distribution - an introduction
This video provides an introduction to the gamma distribution: describing it mathematically, discussing example situations which can be modelled using a gamma in Bayesian inference, then going on to discuss how its two parameters affect the shape of the distribution intuitively, and finall
From playlist Bayesian statistics: a comprehensive course
The Beta Distribution : Data Science Basics
Estimating the probability of a probability. My Patreon : https://www.patreon.com/user?u=49277905 Shoe icons created by Freepik - Flaticon https://www.flaticon.com/free-icons/shoe
From playlist Data Science Basics
Using normal distribution to find the probability
π 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
2020.05.21 Jason Schweinsberg - A Gaussian particle distribution for branching Brownian motion [...]
A Gaussian particle distribution for branching Brownian motion with an inhomogeneous branching rate Motivated by the goal of understanding the evolution of populations undergoing selection, we consider branching Brownian motion in which particles independently move according to one-dime
From playlist One World Probability Seminar