Lecture
Discrete Random Variables: Medical Testing
In course
DEMO: aute nisi minim id
Id mollit officia ipsum nostrud ea esse nisi fugiat dolor enim. Ut duis et do labore qui aute. Deserunt cillum qui et ex voluptate in ex nisi.
Description
This lecture covers the concept of discrete random variables and their frequencies, joint probabilities, and conditional probabilities. It delves into medical testing, discussing the quality of tests characterized by sensitivity and specificity. The instructor explains how to estimate probabilities in medical scenarios using Bayes' theorem.
Instructor
officia commodo nulla
Irure aliqua esse non do cupidatat voluptate sunt aliquip excepteur aute non. Velit velit aliquip et et. Nisi ex esse qui excepteur aliqua. Proident ad irure esse enim commodo qui qui in proident eiusmod exercitation laborum fugiat eu. Cillum deserunt dolore voluptate minim elit reprehenderit. Laboris officia adipisicing sit elit.
Official source
About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Ontological neighbourhood
Related lectures (31)
Random Variables and Expected Value
Introduces random variables, probability distributions, and expected values through practical examples.
Introduction to Inference
Covers the basics of probability theory, random variables, joint probability, and inference.
Probability and Statistics
Covers p-quantile, normal approximation, joint distributions, and exponential families in probability and statistics.
Probability and Statistics: Independence and Conditional Probability
Explores independence and conditional probability in probability and statistics, with examples illustrating the concepts and practical applications.
Probability Theory: Midterm Solutions
Covers the solutions to the midterm exam of a Probability Theory course, including calculations of probabilities and expectations.