Compound probability distributions | Continuous distributions

Normal-exponential-gamma distribution

In probability theory and statistics, the normal-exponential-gamma distribution (sometimes called the NEG distribution) is a three-parameter family of continuous probability distributions. It has a location parameter , scale parameter and a shape parameter . (Wikipedia).

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Using normal distribution to find the probability

πŸ‘‰ 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

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The Normal Distribution (1 of 3: Introductory definition)

More resources available at www.misterwootube.com

From playlist The Normal Distribution

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Find the probability of an event using a normal distribution curve

πŸ‘‰ 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

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The Exponential Distribution and Exponential Random Variables | Probability Theory

What is the exponential distribution? This is one of the most common continuous probability distributions. We'll go over an introduction of the exponential distribution and exponentially distributed random variables in today's probability theory video lesson. The exponential distribution

From playlist Probability Theory

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How to find the probability using a normal distribution curve

πŸ‘‰ 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

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How to find the probability using a normal distribution curve

πŸ‘‰ 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

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Introduction to Exponential Distribution Probabilities

This video introduces the exponential distribution and exponential distribution probabilities. http://mathispower4u.com

From playlist Continuous Random Variables

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Exponential Distribution Percentiles

This video explains how to determine percentiles of an exponential distribution. http://mathispower4u.com

From playlist Continuous Random Variables

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Introduction to Probability and Statistics 131A. Lecture 4. Joint Distribution

UCI Math 131A: Introduction to Probability and Statistics (Summer 2013) Lec 04. Introduction to Probability and Statistics: Joint Distribution View the complete course: http://ocw.uci.edu/courses/math_131a_introduction_to_probability_and_statistics.html Instructor: Michael C. Cranston, Ph.

From playlist Math 131A: Introduction to Probability and Statistics

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Turbulence as Gibbs Statistics of Vortex Sheets - Alexander Migdal

Workshop on Turbulence Topic: Turbulence as Gibbs Statistics of Vortex Sheets Speaker: Alexander Migdal Affiliation: New York University Date: December 11, 2020 For more video please visit http://video.ias.edu

From playlist Mathematics

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Using stochastic chemical kinetic models to explore... (Lecture - 02) by Mukund Thattai

Winter School on Quantitative Systems Biology DATE:04 December 2017 to 22 December 2017 VENUE:Ramanujan Lecture Hall, ICTS, Bengaluru The International Centre for Theoretical Sciences (ICTS) and the Abdus Salam International Centre for Theoretical Physics (ICTP), are organizing a Winter S

From playlist Winter School on Quantitative Systems Biology

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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

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Introduction to Probability and Statistics 131A. Lecture 16. Final Review

UCI Math 131A: Introduction to Probability and Statistics (Summer 2013) Lec 16. Introduction to Probability and Statistics: Lecture 16. Final Review View the complete course: http://ocw.uci.edu/courses/math_131a_introduction_to_probability_and_statistics.html Instructor: Michael C. Cranst

From playlist Math 131A: Introduction to Probability and Statistics

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Introduction to Probability and Statistics 131B. Lecture 01.

UCI Math 131B: Introduction to Probability and Statistics (Summer 2013) Lec 01. Introduction to Probability and Statistics View the complete course: http://ocw.uci.edu/courses/math_131b_introduction_to_probability_and_statistics.html Instructor: Michael C. Cranston, Ph.D. License: Creativ

From playlist Introduction to Probability and Statistics 131B

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Stable Vortex Sheets and Irreversibility of Turbulence - Alexander Migdal

New kinds of vortex sheets with vorticity confined to the boundary layer are proposed and investigated in detail. Exact solutions of the steady Navier-Stokes equations for a planar vortex sheet in arbitrary background strain are found in terms of hypergeometric functions.These solutions ar

From playlist Mathematics

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Tom Claeys: Optimal global rigidity estimates in unitary invariant ensembles

A fundamental question in random matrix theory is to understand how much the eigenvalues of a random matrix fluctuate. I will address this question in the context of unitary invariant ensembles, by studying the global rigidity of the eigenvalues, or in other words the maximal deviation of

From playlist Probability and Statistics

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21. Generalized Linear Models

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 linear model, generalization, and examples of disease occurring rate, prey capture rate, Kyphosis data, etc.

From playlist MIT 18.650 Statistics for Applications, Fall 2016

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Normal Distribution: Mean, Median, Mode, and Standard Deviation From Graph

The video explains how to determine the mean, median, mode and standard deviation from a graph of a normal distribution.

From playlist The Normal Distribution

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Petru Constantinescu - On the distribution of modular symbols and cohomology classes

Motivated by a series of conjectures of Mazur, Rubin and Stein, the study of the arithmetic statistics of modular symbols has received a lot of attention in recent years. In this talk, I will highlight several results about the distribution of modular symbols, including their Gaussian dist

From playlist Γ‰cole d'Γ‰tΓ© 2022 - Cohomology Geometry and Explicit Number Theory

Related pages

Scale parameter | Parabolic cylinder function | Laplace distribution | Exponential distribution | Probability theory | Lomax distribution | Shape parameter | Gamma distribution | Statistics | Probability distribution | Probability density function | Normal distribution | Location parameter | Compound probability distribution