expected value - Learn Data Science with Travis

expected-value

Expected value is a fundamental concept in probability and statistics that represents the average outcome of a random variable over numerous trials. It provides a way to quantify the anticipated value of uncertain events, making it essential in fields such as finance, gambling, and machine learning. The expected value is calculated by multiplying each possible outcome by its probability and summing these products. This concept helps in decision-making processes by allowing individuals to assess the potential benefits or risks associated with different choices. Understanding expected value is crucial for analyzing scenarios involving randomness and uncertainty.

What is the expected value?

Towards Data Science

Even if you are not aware of it, expected value is behind many frequently used concepts such as entropy and the mean squared error .For instance, entropy is the expected value of the information…

Expected Value of Random Variables -Explained Simply

Towards Data Science

The expected value of a random variable is the weighted average of all possible values of the variable. The weight here means the probability of the random variable taking a specific value. What is…

The Devil’s Roulette: a Failure of Expected Value

Towards Data Science

With the propagation of data, technocrats and pop-books about statistics an increasingly large portion of the population are familiar with Expected Value. For the uninitiated Expected Value is the…

Anomaly Detection with Extreme Value Analysis

Towards Data Science

Extreme Value Analysis (EVA) is a statistical methodology that is used primarily to estimate the probability of events that are rarest compared to any previously observed. The fields of application…

The Paths Perspective on Value Learning

Distill

Introduction In the last few years, reinforcement learning (RL) has made remarkable progress, including beating world-champion Go players , controlling robotic hands , and even painting pictures . One...

Expectation and Variance From Zero to Mastery

Towards Data Science

Expectation and variance are one of the basic and yet important topics. It is essential for data scientists to deeply understand the subject in order to tackle statistical problems and understand…

Modeling Expected Goals

Towards Data Science

Using Logistic Regression to predict the probability of a shot resulting in a goal

A Deep Dive into the Science of Statistical Expectation

Towards Data Science

The White Cliffs of Dover (CC BY-SA 3.0) How we come to expect something, what it means to expect anything, and the math that gives rise to the meaning. It was the summer of 1988 when I stepped onto a...

A Guide to Expected Goals

Towards Data Science

Using data to investigate the trends and probabilities of shots and goals

Wordle Words and Expected Value

R-bloggers

Like many people, I’ve gotten sucked into wordle. For those unfamiliar with the game, you are tasked with identifying a five-letter word. You input a guess (which must be a five-letter word) and are t...

Expected goals, gamestate, and predictiveness

R-bloggers

Introduction “The best predictor for future performance is Expected Goals”, authored by Sander Ijtsma of 11tegen11 in 2015, is one of the most notable articles in public soccer analytics. The write-up...

A Gentle Introduction to Expected Value, Variance, and Covariance with NumPy

Machine Learning Mastery

Last Updated on November 16, 2019 Fundamental statistics are useful tools in applied machine learning for a better understanding your data. They are also the tools that provide the foundation for more...