- Learn how base rates can impact a conditional probability
- Calculate probabilities based on a tree diagram
- Calculate probabilities based on Bayes' theorem
This demonstration lets you examine the effects of base rate, true positive rate, and false positive rate on the probability that a person diagnosed with disease \(X\) actually has the disease. The base rate is the proportion of people who have the disease. The true positive rate is the probability that a person with the disease will test positive. The false positive rate is the probability that someone who does not have the disease will test positive. The demonstration is based on \(10,000\) people being tested. A tree diagram showing the results and calculations based on Bayes' theorem are shown. They should always agree.
You can change the initial values and then press the "Calculate" button.
The Bayes' Theorem demonstration starts by displaying the results for the default base rate, true positive rate and the false positive rate as shown in the screenshot below. You can change any of these three numbers and click the "Calculate" button to get the results based on the changes you make.
Online Statistics Education: A Multimedia Course of Study (http://onlinestatbook.com/). Project Leader: David M. Lane, Rice University.