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Learn how to measure uncertainty in experiments using probabilities, events, and sample spaces. Explore theoretical, empirical, and subjective probabilities, and how to calculate complements and inequalities.
Learn the basic rules of probability, such as the impossible and certain events, the sum and product rules, the addition and multiplication rules, and the conditional probability. See examples and applications of these rules in the context of party affiliation and Venn diagrams.
Learn how to use the law of total probability to calculate the probability of an event based on its marginal and conditional probabilities. See examples, definitions, and related concepts in probability theory.
Probability is the branch of mathematics concerning events and numerical descriptions of how likely they are to occur. The probability of an event is a number between 0 and 1; the larger the probability, the more likely an event is to occur. [note 1][1][2] A simple example is the tossing of a fair (unbiased) coin.
How to use three probability laws (the rules of addition, subtraction, and multiplication) to solve probability problems. Includes problems with solutions.
The standard probability axioms are the foundations of probability theory introduced by Russian mathematician Andrey Kolmogorov in 1933. [1] These axioms remain central and have direct contributions to mathematics, the physical sciences, and real-world probability cases.
Learn how to calculate probabilities of events using the rules of probability, such as addition, multiplication, and complement. See examples of coin tossing, blood types, and periodontal status.
