Frequentist probability or frequentism is an interpretation of probability; it defines an event's probability as the limit of its relative frequency in many trials (the long-run probability). Probabilities can be found (in principle) by a repeatable objective process (and are thus ideally devoid of opinion). The continued use of frequentist methods in scientific inference, however, has been called into question. The development of the frequentist account was motivated by the problems and paradoxes of the previously dominant viewpoint, the classical interpretation. In the classical interpretation, probability was defined in terms of the principle of indifference, based on the natural symmetry of a problem, so, e.g. the probabilities of dice games arise from the natural symmetric 6-sidedness of the cube. This classical interpretation stumbled at any statistical problem that has no natural symmetry for reasoning. (Wikipedia).
Bayesian vs frequentist statistics probability - part 1
This video provides an intuitive explanation of the difference between Bayesian and classical frequentist statistics. If you are interested in seeing more of the material, arranged into a playlist, please visit: https://www.youtube.com/playlist?list=PLFDbGp5YzjqXQ4oE4w9GVWdiokWB9gEpm Unfo
From playlist Bayesian statistics: a comprehensive course
(PP 3.1) Random Variables - Definition and CDF
(0:00) Intuitive examples. (1:25) Definition of a random variable. (6:10) CDF of a random variable. (8:28) Distribution of a random variable. A playlist of the Probability Primer series is available here: http://www.youtube.com/view_play_list?p=17567A1A3F5DB5E4
From playlist Probability Theory
Bayesian vs frequentist statistics probability - part 2
This video provides a short introduction to the similarities and differences between Bayesian and Frequentist views on probability. If you are interested in seeing more of the material, arranged into a playlist, please visit: https://www.youtube.com/playlist?list=PLFDbGp5YzjqXQ4oE4w9GVWdi
From playlist Bayesian statistics: a comprehensive course
Bayesian vs frequentist statistics
This video provides an intuitive explanation of the difference between Bayesian and classical frequentist statistics. If you are interested in seeing more of the material, arranged into a playlist, please visit: https://www.youtube.com/playlist?list=PLFDbGp5YzjqXQ4oE4w9GVWdiokWB9gEpm Un
From playlist Bayesian statistics: a comprehensive course
UNIFORM Probability Distribution for Continuous Random Variables (10-2)
The Uniform Distribution models events or intervals that are equally likely to occur, such as the time spent waiting for a shuttle to arrive. The probability equals the area under the graph of f(x); the height of f(x) is a constant. At his private island, Ted runs a shuttle service tenderi
From playlist Continuous Probability Distributions in Statistics (WK 10 - QBA 237)
Bayesians, Frequentists, and Parallel Universes
My Patreon : https://www.patreon.com/user?u=49277905 Icon Resources : https://www.flaticon.com/authors/prettycons https://www.freepik.com https://www.flaticon.com/authors/photo3idea-studio
From playlist Bayesian Statistics
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
Uniform Probability Distribution Examples
Overview and definition of a uniform probability distribution. Worked examples of how to find probabilities.
From playlist Probability Distributions
Bayes Billiards with Tom Crawford
Bayes' Theorem allows us to assign a probability to an unknown fact. Thomas Bayes himself described an experiment with a billiard table, which is brilliantly explained by Hannah Fry and Matt Parker here https://www.youtube.com/watch?v=7GgLSnQ48os Brian Cox and David Spiegelhalter did a 1
From playlist Collaborations
IS CHESS A GAME OF CHANCE? Classical vs Frequentist vs Bayesian Probability
Learn more about probability - and so much more - at http://www.brilliant.org/treforbazett. My thanks to Brilliant for sponsoring today's video. Check out my MATH MERCH line in collaboration with Beautiful Equations ►https://www.beautifulequation.com/pages/trefor What, exactly, is prob
From playlist Discrete Math (Full Course: Sets, Logic, Proofs, Probability, Graph Theory, etc)
What are confidence intervals? Actually.
See all my videos at https://www.zstatistics.com/ 1:01 Intuition 4:46 How are they calculated 14:28 Confidence interval examples 18:50 Frequentist vs Bayesian ERRATA: The confidence interval created for the population proportion at 13:51 should be 0.03 to 0.21. HEALTH STATS IQ PLAYLIST
From playlist Health Stats IQ
18. Bayesian Statistics (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 Bayesian confidence regions and Bayesian estimation. License: Creative Commons BY-NC-SA More information at
From playlist MIT 18.650 Statistics for Applications, Fall 2016
2a Data Analytics Reboot: Probability
Lecture on the nature of probability? What is probability? How can we calculate it. Data Analytics and Geostatistics is an undergraduate course that I teach fall and spring semesters at The University of Texas at Austin. We build up fundamental spatial, subsurface, geoscience and enginee
From playlist Data Analytics and Geostatistics
EXPONENTIAL Probability Distribution for Continuous Random Variables (10-3)
An Exponential Probability Distribution models interval of time between occurrences of an event, such as the length of stay for cruise guests in pool lounge chairs. The mean and the standard deviation are equal and it is heavily right skewed. Our application is how long it takes to restock
From playlist Continuous Probability Distributions in Statistics (WK 10 - QBA 237)
11d Machine Learning: Bayesian Linear Regression
Lecture on Bayesian linear regression. By adopting the Bayesian approach (instead of the frequentist approach of ordinary least squares linear regression) we can account for prior information and directly model the distributions of the model parameters by updating with training data. Foll
From playlist Machine Learning
UNIFORM Probability Distribution for Discrete Random Variables (9-5)
Uniform Probability Distribution: (i.e., a rectangular distribution) is a probability distribution involving one random variable with a constant probability. Each potential outcome is equally likely, such as flipping coin and getting heads is always 50/50. On Chaos Night, Dante experiment
From playlist Discrete Probability Distributions in Statistics (WK 9 - QBA 237)
Bayesian Statistics: An Introduction
See all my videos here: http://www.zstatistics.com/videos/ 0:00 Introduction 2:25 Frequentist vs Bayesian 5:55 Bayes Theorum 10:45 Visual Example 15:05 Bayesian Inference for a Normal Mean 24:30 Conjugate priors 32:55 Credible Intervals
From playlist Statistical Inference (7 videos)