--- title: Conditional Probability description: Conditional probability measures the likelihood of an event occurring given that another event has already occurred. Learners will understand how to calculate dependent probabilities and apply these concepts to real-world scenarios. category: mathematics subcategory: probability-theory difficulty: beginner, intermediate, advanced url: /subject/conditional-probability --- # Conditional Probability Conditional probability measures the likelihood of an event occurring given that another event has already occurred. Learners will understand how to calculate dependent probabilities and apply these concepts to real-world scenarios. ## Available Resources 2 Courses • 6 Websites ## Websites ### 1. Khan Academy - Conditional Probability Khan Academy unit of short videos and auto-graded exercises on conditional probability and independence. Works through two-way tables, tree diagrams and the multiplication rule so the learner can compute P(A|B) and test whether two events are independent. **Difficulty:** Beginner | **Price:** Free **Link:** https://www.khanacademy.org/math/statistics-probability/probability-library/conditional-probability-independence **Tags:** conditional-probability, independence, tree-diagrams, introductory-statistics ### 2. Seeing Theory An interactive, D3.js-based walkthrough of probability and statistics in six chapters, from basic probability and distributions through frequentist inference, Bayesian inference and regression analysis. Parameters are manipulable, so sampling behaviour and fit are visible directly. **Difficulty:** Beginner | **Price:** Free **Link:** https://seeing-theory.brown.edu/basic-probability/index.html **Tags:** probability, statistics, data-visualization, regression, bayesian-inference ### 3. Conditional Probability — Introduction to Probability, Statistics and Random Processes **Author:** Hossein Pishro-Nik The conditional-probability chapter of a free full-text university textbook, covering the definition, chain rule, law of total probability, Bayes' rule, and independence, each followed by a bank of fully worked solved problems for self-testing. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://www.probabilitycourse.com/chapter1/1_4_0_conditional_probability.php **Tags:** conditional-probability, bayes-rule, law-of-total-probability, independence ### 4. Seeing Theory: Compound Probability (Interactive) **Author:** Daniel Kunin Interactive D3 visualisations from a Brown University project. Dragging events across a sample space shows conditioning shrinking and rescaling it in real time, giving a geometric picture of P(A|B), joint events, and independence. **Difficulty:** Beginner | **Language:** English | **Price:** Free **Link:** https://seeing-theory.brown.edu/compound-probability/index.html **Tags:** conditional-probability, interactive-visualization, independence, set-theory ### 5. probabilitycourse.com ProbabilityCourse.com is an online learning resource that provides a structured probability course with clear explanations, worked examples, and practice problems covering topics from basics to advanced theory. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://probabilitycourse.com **Tags:** websites, technology-computer-science, data-science--ai ### 6. Wolfram MathWorld **Author:** Eric W. Weisstein MathWorld is an online mathematics encyclopedia from Wolfram Research offering detailed, browsable articles on topics across the math spectrum, including algebra, geometry, calculus, and number theory. Each entry includes definitions, theorems, formulas, diagrams, worked examples, and links to further reading. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://mathworld.wolfram.com **Tags:** mathematics-reference, encyclopedia, abstract-algebra, number-theory, geometry ## Courses ### 1. Probabilistic Systems Analysis and Applied Probability (MIT 6.041SC) **Author:** John Tsitsiklis Modeling and analysis of uncertainty: probability models, discrete and continuous random variables, Bayesian inference, limit theorems and random processes. Designed for independent study, with lecture videos, slides, recitation and tutorial problems, problem sets and exams with solutions, and TA problem-solving videos. **Difficulty:** Intermediate | **Price:** Free **Link:** https://ocw.mit.edu/courses/6-041sc-probabilistic-systems-analysis-and-applied-probability-fall-2013/ **Tags:** probability, random-variables, bayesian-inference, limit-theorems, random-processes, statistical-inference ### 2. An Intuitive Introduction to Probability **Author:** Karl Schmedders University of Zurich course taught by Karl Schmedders that builds probability from everyday examples: basic rules, conditional probability, applications, discrete random variables, and the normal distribution. Learners finish able to compute and interpret probabilities in practical decisions. **Difficulty:** Beginner | **Language:** English | **Price:** Free **Link:** https://www.coursera.org/learn/introductiontoprobability **Tags:** probability, conditional-probability, discrete-random-variables, normal-distribution --- *This content is part of Dantes.io - Your Treasure Map to Knowledge* *Curated by humans at Dantes.io. Personal study use welcome; republishing this curation requires permission (team@dantes.io).* View this page online: https://dantes.io/subject/conditional-probability