A quick introduction to expected value formulas.
From playlist Basic Statistics (Descriptive Statistics)
Expected Value Example and Intuitive Explanation
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Expected Value Example and Intuitive Explanation
From playlist Statistics
How to find expected value by hand and in Excel using SUMPRODUCT.
From playlist Basic Statistics (Descriptive Statistics)
Expected Value of the Bernoulli Distribution | Probability Theory
How do we derive the mean or expected value of a Bernoulli random variable? We'll be going over that in today's probability theory lesson! Remember a Bernoulli random variable is a random variable that is equal to 1 (success) with probability p and equal to 0 (failure) with probability 1-
From playlist Probability Theory
Expectation Values in Quantum Mechanics
Expectation values in quantum mechanics are an important tool, which help us to mathematically describe measurements of quantum systems. You can think of expectation values as the average of all possible outcomes of a measurement, weighted by their respective probabilities. Contents: 00:
From playlist Quantum Mechanics, Quantum Field Theory
Thanks to all of you who support me on Patreon. You da real mvps! $1 per month helps!! :) https://www.patreon.com/patrickjmt !! In this video, I show the formula of expected value, and compute the expected value of a game. The final answer represents the net transaction to you!! It mea
From playlist All Videos - Part 8
Expected Value of the Exponential Distribution | Exponential Random Variables, Probability Theory
What is the expected value of the exponential distribution and how do we find it? In today's video we will prove the expected value of the exponential distribution using the probability density function and the definition of the expected value for a continuous random variable. It's gonna b
From playlist Probability Theory
Expected Value of a Binomial Probability Distribution
Today, we derive the formula to find the expected value or the mean of a discrete random variable which follows the binomial probability distribution.
From playlist Probability
Unit 9: Value of Information, Video 4: Expected Value of Perfect Information
MIT IDS.333 Risk and Decision Analysis, Fall 2021 Instructor: Richard de Neufville View the complete course: https://ocw.mit.edu/courses/ids-333-risk-and-decision-analysis-fall-2021/ YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP62jwhTqp8_1kwrkDkxZhpQC Perfect informa
From playlist MIT IDS.333 Risk and Decision Analysis, Fall 2021
Value of Information in the Earth Sciences
Overview, narrated by Tapan Mukerji Eidsvik, J., Mukerji, T. and Bhattacharjya, D., 2015. Value of information in the earth sciences: Integrating spatial modeling and decision analysis. Cambridge University Press.
From playlist Uncertainty Quantification
Unit 9: Value of Information 5, Video 5: Is Test Worthwhile?
MIT IDS.333 Risk and Decision Analysis, Fall 2021 Instructor: Richard de Neufville View the complete course: https://ocw.mit.edu/courses/ids-333-risk-and-decision-analysis-fall-2021/ YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP62jwhTqp8_1kwrkDkxZhpQC This video prov
From playlist MIT IDS.333 Risk and Decision Analysis, Fall 2021
ReBeL - Combining Deep Reinforcement Learning and Search for Imperfect-Information Games (Explained)
#ai #technology #poker This paper does for Poker what AlphaZero has done for Chess & Go. The combination of Self-Play Reinforcement Learning and Tree Search has had tremendous success in perfect-information games, but transferring such techniques to imperfect information games is a hard p
From playlist Papers Explained
Deep Uncertainty of Climate Sensitivity Estimates: Sources and Implications
Klaus Keller, Penn State University, delivers a lecture entitled, "Deep Uncertainty of Climate Sensitivity Estimates: Sources and Implications", during the YCEI conference, "Uncertainty in Climate Change: A Conversation with Climate Scientists and Economists".
From playlist Uncertainty in Climate Change: A Conversation with Climate Scientists and Economists
Ulrike von Luxburg: Statistics on graphs and networks (II)
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 SPECIAL 7th European congress of Mathematics Berlin 2016.
DeepMind x UCL RL Lecture Series - Planning & models [8/13]
Research Engineer Matteo Hessel explains how to learn and use models, including algorithms like Dyna and Monte-Carlo tree search (MCTS). Slides: https://dpmd.ai/planningmodels Full video lecture series: https://dpmd.ai/DeepMindxUCL21
From playlist Learning resources
Olfactory Search and Navigation (Lecture 2) by Antonio Celani
PROGRAM ICTP-ICTS WINTER SCHOOL ON QUANTITATIVE SYSTEMS BIOLOGY (ONLINE) ORGANIZERS Vijaykumar Krishnamurthy (ICTS-TIFR, India), Venkatesh N. Murthy (Harvard University, USA), Sharad Ramanathan (Harvard University, USA), Sanjay Sane (NCBS-TIFR, India) and Vatsala Thirumalai (NCBS-TIFR, I
From playlist ICTP-ICTS Winter School on Quantitative Systems Biology (ONLINE)
Lecture 07: Planning and Learning with Tabular Methods
Seventh lecture video on the course "Reinforcement Learning" at Paderborn University during the summer term 2020. Source files are available here: https://github.com/upb-lea/reinforcement_learning_course_materials
From playlist Reinforcement Learning Course: Lectures (Summer 2020)
Kerrie Mengersen: Bayesian Modelling
Abstract: This tutorial will be a beginner’s introduction to Bayesian statistical modelling and analysis. Simple models and computational tools will be described, followed by a discussion about implementing these approaches in practice. A range of case studies will be presented and possibl
From playlist Probability and Statistics