Theory of probability distributions | Independence (probability theory) | Covariance and correlation

Tail dependence

In probability theory, the tail dependence of a pair of random variables is a measure of their comovements in the tails of the distributions. The concept is used in extreme value theory. Random variables that appear to exhibit no correlation can show tail dependence in extreme deviations. For instance, it is a stylized fact of stock returns that they commonly exhibit tail dependence. (Wikipedia).

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How to Choose Long Tail Keywords For Explosive Search Traffic

In this tutorial, you’ll learn how to find and choose long-tail keywords with high traffic potential and/or low competition (even if they have low individual search volume). A common misconception is that long-tail keywords must be a certain length (word count) in order to be classified

From playlist Keyword Research Tutorials For SEO

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MINI-LESSON 2: Fat Tails, a Very, Very Introductory Presentation.

What are Fat Tails? This is very introductory. See the whole book (gets technical beyond Chapter 5) https://researchers.one/articles/20.01.00018

From playlist MINI LECTURES IN PROBABILITY

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QRM 4-3: A Bestiary of Tails

Welcome to Quantitative Risk Management (QRM). There is so much confusion about tails, that it is time to clarify what we are speaking about. Heavy tails, long tails and fat tails are not the same thing from a statistical and probabilistic point of view. In mathematics we need to be preci

From playlist Quantitative Risk Management

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Covariance (1 of 17) What is Covariance? in Relation to Variance and Correlation

Visit http://ilectureonline.com for more math and science lectures! To donate:a http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 We will learn the difference between the variance and the covariance. A variance (s^2) is a measure of how spread out the numbers of

From playlist COVARIANCE AND VARIANCE

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How Increasing Benefits Increases the Risk of Ruin

Explains why you do not decrease tail risks by increasing benefits, you decrease tail risk by decreasing tail risk. This is a very short exposition of a fallacy quite generalized, but particularly present in discussions concerning the benefits of GMO. Biologists dealing with probability ha

From playlist QUANT FINANCE TOPICS

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Path Dependence and Tipping Points

In this video I explain what physicists mean by "path dependence" or "hysteresis" and "tipping points". I go through the common example for hysteresis using the magnetization of a ferromagnet and talk about tipping points in climate models. A list with tipping points in climate models is

From playlist My Favorites

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Momentum (1 of 16) An Explanation

This video gives a complete explanation of momentum. It also includes an example momentum problem. Momentum is a quantity of matter arising from its mass and velocity. The momentum of an object is directly proportional to its mass and velocity. Momentum is a vector quantity. Impulse is th

From playlist Momentum, Impulse, Inelastic and Elastic Collisions

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Physics - Fluid Dynamics (19 of 32) The Drag Coefficient

Visit http://ilectureonline.com for more math and science lectures! In this video I will explain how different shaped objects have different drag coefficients. Next video in this series can be seen at: http://youtu.be/5IcpUjIo7jM

From playlist PHYSICS 34 FLUID DYNAMICS

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Pavel Krupskiy - Conditional Normal Extreme-Value Copulas.

Dr Pavel Krupskiy (University of Melbourne) presents “Conditional Normal Extreme-Value Copulas”, 14 August 2020. Seminar organised by UNSW Sydney.

From playlist Statistics Across Campuses

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12. Testing Goodness of Fit (cont.)

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 Kolmogorov-Lilliefors test, Quantile-Quantile plots, and Kai-squared goodness-of-fit test. License: Creative

From playlist MIT 18.650 Statistics for Applications, Fall 2016

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Thomas Mikosch : Asymptotic theory for the sample covariance matrix of a heavy-tailed [...]

Find this video and other talks given by worldwide mathematicians on CIRM's Audiovisual Mathematics Library: http://library.cirm-math.fr. And discover all its functionalities: - Chapter markers and keywords to watch the parts of your choice in the video - Videos enriched with abstracts, b

From playlist Probability and Statistics

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What is the probability of two events occurring together? First determine if the events and independent or dependant on eachother. Does replacement occur? Do you need product or addition rules? All this answered in this probability math lesson. To donate to the tecmath channel: https:

From playlist Probability

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Risks and fat tails

This is the video of my talk at the Conference on Complex Systems 2020 (CCS2020), in the satellite event organised by Alfredo J. Morales (MIT) and Rosa M. Benito (Technical University of Madrid). For privacy reasons, I have cut the video, not to show the pictures of the other participants

From playlist Talks and Interviews

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Statistics: Ch 4 Probability in Statistics (40 of 74) Independent? Mutually Exclusive?

Visit http://ilectureonline.com for more math and science lectures! To donate: http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 We will summarize the differences between independent and mutually exclusive events. Mutually exclusive - 2 events cannot occur toget

From playlist STATISTICS CH 4 STATISTICS IN PROBABILITY

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Spectral Large Deviations for Sparse Random Matrices by Kyeongsik Nam

PROGRAM: TOPICS IN HIGH DIMENSIONAL PROBABILITY ORGANIZERS: Anirban Basak (ICTS-TIFR, India) and Riddhipratim Basu (ICTS-TIFR, India) DATE & TIME: 02 January 2023 to 13 January 2023 VENUE: Ramanujan Lecture Hall This program will focus on several interconnected themes in modern probab

From playlist TOPICS IN HIGH DIMENSIONAL PROBABILITY

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Compound probability of independent events | Probability and Statistics | Khan Academy

You'll become familiar with the concept of independent events, or that one event in no way affects what happens in the second event. Keep in mind, too, that the sum of the probabilities of all the possible events should equal 1. Practice this lesson yourself on KhanAcademy.org right now:

From playlist High school statistics | High School Math | Khan Academy

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One Tailed and Two Tailed Tests, Critical Values, & Significance Level - Inferential Statistics

This statistics video tutorial explains when you should use a one tailed test vs a two tailed test when solving problems associated with hypothesis testing. It all depends on the statement associated with the alternative hypothesis. This video also discusses the critical values and signi

From playlist Statistics

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Independent and Dependent Events (really understand this stuff)

This video will explain the differences between independent and dependent events. Most students need help understanding basic probability so this video explains the basics. For more videos like this please visit TabletClass Math http://www.tabletclass.com

From playlist GED Prep Videos

Related pages

Random variable | Correlation | Extreme value theory | Probability distribution | Dependency relation