Teaching Bayes' Rule using Mosaic Plots

11/30/2021
by   Edward D. White, et al.
0

Students taking statistical courses orientated for business or economics often find the standard presentation of Bayes' Rule challenging. This key concept involves understanding multiple conditional probabilities and how they constitute an unconditional sample space. Many textbooks try to aid the comprehension of Bayes' Rule by illustrating these probabilities with tree diagrams. In our opinion, these diagrams fall short in fully assisting the students to visualize Bayes' Rule. In this article, we demonstrate a graphical approach that we have successfully used in the classroom, but is neglected in introductory texts. This approach uses mosaic plots to show the weighting of the conditional probabilities and greatly aids the student in understanding the sample space and its associated probabilities.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/29/2010

Kernel Bayes' rule

A nonparametric kernel-based method for realizing Bayes' rule is propose...
research
11/28/2014

Probability Theory without Bayes' Rule

Within the Kolmogorov theory of probability, Bayes' rule allows one to p...
research
01/30/2013

Bayes-Ball: The Rational Pastime (for Determining Irrelevance and Requisite Information in Belief Networks and Influence Diagrams)

One of the benefits of belief networks and influence diagrams is that so...
research
12/02/2022

The generalized IFS Bayesian method and an associated variational principle covering the classical and dynamical cases

We introduce a general IFS Bayesian method for getting posterior probabi...
research
12/24/2017

Judicious Judgment Meets Unsettling Updating: Dilation, Sure Loss, and Simpson's Paradox

Statistical learning using imprecise probabilities is gaining more atten...
research
12/30/2019

Bayesian Tensor Network with Polynomial Complexity for Probabilistic Machine Learning

It is known that describing or calculating the conditional probabilities...

Please sign up or login with your details

Forgot password? Click here to reset