The use of evidence under Bayes' theorem relates to the probability of finding evidence in relation to the accused, where Bayes' theorem concerns the probability of an event and its inverse. Specifically, it compares the probability of finding particular evidence if the accused were guilty, versus if they were not guilty. An example would be the probability of finding a person's hair at the scene, if guilty, versus if just passing through the scene. Another issue would be finding a person's DNA where they lived, regardless of committing a crime there. (Wikipedia).
Think more rationally with Bayes’ rule | Steven Pinker
The formula for rational thinking explained by Harvard professor Steven Pinker. Subscribe to Big Think on YouTube ► https://www.youtube.com/channel/UCvQECJukTDE2i6aCoMnS-Vg?sub_confirmation=1 Up next, The war on rationality ► https://youtu.be/qdzNKQwkp-Y In his explanation of Bayes' theo
From playlist Get smarter, faster
Conditional Probability: Bayes’ Theorem – Disease Testing (Table and Formula)
This video shows how to determine conditional probability using a table and using Bayes' theorem. @mathipower4u
From playlist Probability
Prob & Stats - Bayes Theorem (4 of 24) A More Comprehensive Equation
Visit http://ilectureonline.com for more math and science lectures! In this video I will explain a more comprehensive Bayes theorem probability equation. The equation states the PROBILITY that someone WILL HAVE THE DISEASE IF THEY TEST POSITIVE is equal to someone will TEST POSITIVE WHEN
From playlist PROB & STATS 4 BAYES THEOREM
Prob & Stats - Bayes Theorem (1 of 24) What is Bayes Theorem?
Visit http://ilectureonline.com for more math and science lectures! In this video I will explain what is and define the symbols of Bayes Theorem. Bayes Theorem calculates the probability of an event or the predictive value of an outcome of a test based on prior knowledge of condition rela
From playlist PROB & STATS 4 BAYES THEOREM
This lesson explains Bayes' Theorem intuitively and then verifies the result using Bayes' Theorem. Site: http://mathispower4u.com
From playlist Probability
Bayes' Theorem and Cancer Screening
Thanks to all of you who support me on Patreon. You da real mvps! $1 per month helps!! :) https://www.patreon.com/patrickjmt !! Bayes' Theorem and Cancer Screening. A very real life example of Bayes' Theorem in action. ** According to some data I found online (not sure how accurate i
From playlist All Videos - Part 1
An introduction to the use of Bayes' rule in statistics. If you are interested in seeing more of the material, arranged into a playlist, please visit: https://www.youtube.com/playlist?list=PLFDbGp5YzjqXQ4oE4w9GVWdiokWB9gEpm Unfortunately, Ox Educ is no more. Don't fret however as a whol
From playlist Bayesian statistics: a comprehensive course
Bayes' Theorem - The Simplest Case
►Second Bayes' Theorem example: https://www.youtube.com/watch?v=k6Dw0on6NtM ►Third Bayes' Theorem example: https://www.youtube.com/watch?v=HaYbxQC61pw ►FULL Discrete Math Playlist: https://www.youtube.com/watch?v=rdXw7Ps9vxc&list=PLHXZ9OQGMqxersk8fUxiUMSIx0DBqsKZS Bayes' Theorem is an inc
From playlist Discrete Math (Full Course: Sets, Logic, Proofs, Probability, Graph Theory, etc)
7 Bayes' rule in inference the prior and denominator
This provides a short introduction into the use of Bayes' rule in inference, by going through an example where the prior and denominator in the formula are explained. If you are interested in seeing more of the material, arranged into a playlist, please visit: https://www.youtube.com/play
From playlist Bayesian statistics: a comprehensive course
Bayes Theorem, Three-state variable (FRM T2-9c)
[https://trtl.bz/220122-bayes-three-states] This explores the answer to Miller's sample question in Chapter 6 of http://amzn.to/2C88m0i. There are three types of managers: Out-performers (MO), in-line performers (MI) and under-performers (MU). The prior probability that a manager is an out
From playlist Quantitative Analysis (FRM Topic 2)
Data Mining with Weka (3.3: Using probabilities)
Data Mining with Weka: online course from the University of Waikato Class 3 - Lesson 3: Using probabilities https://weka.waikato.ac.nz/ Slides (PDF): https://www.cs.waikato.ac.nz/ml/weka/mooc/dataminingwithweka/ https://twitter.com/WekaMOOC https://wekamooc.blogspot.co.nz/ Department
From playlist Data Mining with Weka
You Know I’m All About that Bayes: Crash Course Statistics #24
Today we’re going to talk about Bayes Theorem and Bayesian hypothesis testing. Bayesian methods like these are different from how we've been approaching statistics so far, because they allow us to update our beliefs as we gather new information - which is how we tend to think naturally abo
From playlist Statistics
Naive Bayes Classifier in Python | Naive Bayes Algorithm | Machine Learning Algorithm | Edureka
** Machine Learning Training with Python: https://www.edureka.co/data-science-python-certification-course ** This Edureka video will provide you with a detailed and comprehensive knowledge of Naive Bayes Classifier Algorithm in python. At the end of the video, you will learn from a demo ex
From playlist Machine Learning Algorithms in Python (With Demo) | Edureka
O'Reilly Webcast: Bayesian Statistics Made Simple
Join Allen Downey, author of Think Stats: Probability and Statistics for Programmers for an introduction to Bayesian statistics using Python. Bayesian statistical methods are becoming more common and more important, but there are not many resources to help beginners get started. People who
From playlist O'Reilly Webcasts 2
Bayes Theorem, adding a bit of complexity (FRM T2- 9b)
[Here is my XLS at http://trtl.bz/122717-YT-Bayes-2nd-Star-Mgr] and Here is the question: "You are an analyst at Astra Fund of Funds. Based on an examination of historical data, you determine that all fund managers fall into one of two groups. Stars are the best managers. The probability t
From playlist Quantitative Analysis (FRM Topic 2)
Bayes in Science and Everyday Life: Crash Course Statistics #25
Today we're going to finish up our discussion of Bayesian inference by showing you how we can it be used for continuous data sets and be applied both in science and everyday life. From A/B testing of websites and getting a better understanding of psychological disorders to helping with lan
From playlist Statistics
Bayes Theorem: Simple test for disease (FRM T2-9)
[my xls is here http://trtl.bz/2BO9LNq] Bayes Theorem updates a conditional probability with new evidence. In this case, the conditional probability (disease | positive test result) equals the joint probability (disease, positive test result) divided by the unconditional probability (posit
From playlist Quantitative Analysis (FRM Topic 2)
2c Data Analytics Reboot: Bayesian Probability
Lecture on Bayesian probability. From the product rule to the derivation of Bayes' Theorem, to solving a variety of probability problems and making observations. Bayesian approaches for updating prior probabilities with new information. Follow along with the demonstration workflow in Pyt
From playlist Data Analytics and Geostatistics
Prob & Stats - Bayes Theorem (5 of 24) A More Comprehensive Equation: Another Method
Visit http://ilectureonline.com for more math and science lectures! In this video I will show there are different methods to calculate the PROBILITY that someone WILL HAVE THE DISEASE IF THEY TEST POSITIVE (just because someone tests positive doesn't mean they will have the disease). The
From playlist PROB & STATS 4 BAYES THEOREM