In probability theory, a hyper-Erlang distribution is a continuous probability distribution which takes a particular Erlang distribution Ei with probability pi. A hyper-Erlang distributed random variable X has a probability density function given by where each pi > 0 with the pi summing to 1 and each of the Eli being an Erlang distribution with li stages each of which has parameter λi. (Wikipedia).
Hypergeometric Distribution EXPLAINED!
See all my videos here: http://www.zstatistics.com/videos/ 0:00 Introduction 1:02 Quick Rundown 2:57 Probability Mass Function calculation 5:22 Cumulative Distribution Function calculation 6:48 Problem Question! Puck's flush: 0.0197
From playlist Distributions (10 videos)
(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
Statistics - 5.4.1 The Hypergeometric Distribution
The Hypergeometric distribution is used in a similar way to the binomial distribution. The biggest difference is that the population is fixed and therefore the trials are dependent. We will learn what values we need to know and how to calculate the results for probabilities of exactly one
From playlist Applied Statistics (Entire Course)
(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
(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
Ruby Conference 2008 - What All Rubyists Should Know About Threads
By: Jim Weirich Help us caption & translate this video! http://amara.org/v/GH3R/
From playlist Ruby Conference 2008
When should you turn to functional programming approaches? Steve Vinoski tells of his own experiences with distributed application development and why Erlang eased (many of) his headaches.
From playlist Programming Podcast
Random Incidence Under Erlang Arrivals
MIT 6.041SC Probabilistic Systems Analysis and Applied Probability, Fall 2013 View the complete course: http://ocw.mit.edu/6-041SCF13 Instructor: Jimmy Li License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.041SC Probabilistic Systems Analysis and Applied Probability, Fall 2013
In this video we discuss the Gaussian (AKA Normal) probability distribution function. We show how it relates to the error function (erf) and discuss how to use this distribution analytically and numerically (for example when analyzing real-life sensor data or performing simulation of stoc
From playlist Probability
Mike Amundsen (Layer 7) Interview - OSCON 2014
The Principal API Architect at Layer 7 Technologies sits down for an interview at the 2014 O'Reilly Open Source Convention. Watch more from OSCON: http://goo.gl/HlGwvP In this interview, Amundsen discusses hypermedia APIs, inter-service dependency, and more. An internationally known auth
From playlist OSCON 2014
LambdaConf 2015 - The Meaning of LFE Zeeshan Lakhani
Do you enjoy Lisp-based languages, built on s-expressions and homoiconicity? Do you like writing syntactic abstractions with pattern matching? What if you could use a Lisp to write a fault-tolerant, highly-available distributed datastore? Welcome to the wonderful world of LFE (Lisp-Flavore
From playlist LambdaConf 2015
ElixirConf 2016 - pg2 and You: Getting Distributed with Elixir by Eric Entin
pg2 and You: Getting Distributed with Elixir by Eric Entin Erlang's pg2 module provides distributed process groups and is a key technology underlying Phoenix's default PubSub adapter, which powers the Channels API that we know and love. Together, we'll take a guided tour of pg2's capabili
From playlist ElixirConf 2016
What are Hyperbolas? | Ch 1, Hyperbolic Trigonometry
This is the first chapter in a series about hyperbolas from first principles, reimagining trigonometry using hyperbolas instead of circles. This first chapter defines hyperbolas and hyperbolic relationships and sets some foreshadowings for later chapters This is my completed submission t
From playlist Summer of Math Exposition 2 videos
Francesco Cesarini interviewed at OSCON 2013
http://www.oscon.com Francesco Cesarini is the founder of Erlang Solutions Ltd. He has used Erlang on a daily basis since 1995, starting as an intern at Ericsson's computer science laboratory, the birthplace of Erlang. He moved on to Ericsson's Erlang training and consulting arm working on
From playlist Open Source Convention (OSCON) 2013
OCR MEI Statistics Minor J: Poisson Distribution: 03 EXTENSION Deriving Var(X)
https://www.buymeacoffee.com/TLMaths Navigate all of my videos at https://sites.google.com/site/tlmaths314/ Like my Facebook Page: https://www.facebook.com/TLMaths-1943955188961592/ to keep updated Follow me on Instagram here: https://www.instagram.com/tlmaths/ Many, MANY thanks to Dea
From playlist OCR MEI Statistics Minor J: Poisson Distribution
Programming Elixir: The magic of today's tonic
Presenter(s): Katie Miller URL: https://lca2014.linux.org.au/schedule/30072/view_talk Elixir is a new arrival on the programming language scene but many of the features that have its devotees raving are actually old favourites for functional fans. Pragmatic Programmer Dave Thomas has laud
From playlist erlang
Erlang Master Class 2: Video 6 - Discussion
http://www.cs.kent.ac.uk/ErlangMasterClasses These Master Classes will show you how Erlang can be used in practice to solve larger problems. The examples provide 'capstones' for different aspects of Erlang: functional programming, concurrent programming and larger-scale programming with O
From playlist Erlang Master Class
Erlang Master Class 3: Video 6 - Discussion
http://www.cs.kent.ac.uk/ErlangMasterClasses These Master Classes will show you how Erlang can be used in practice to solve larger problems. The examples provide 'capstones' for different aspects of Erlang: functional programming, concurrent programming and larger-scale programming with O
From playlist Erlang Master Class
The Normal Distribution (1 of 3: Introductory definition)
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From playlist The Normal Distribution