Ad
related to: general addition rule of probability
Search results
Results From The WOW.Com Content Network
This is called the addition law of probability, or the sum rule. That is, the probability that an event in A or B will happen is the sum of the probability of an event in A and the probability of an event in B, minus the probability of an event that is in both A and B. The proof of this is as follows: Firstly,
Probability is the branch of mathematics and statistics 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] This number is often expressed as a percentage (%), ranging from 0% to ...
Sum rule may refer to: Sum rule in differentiation, Differentiation rules #Differentiation is linear; Sum rule in integration, see Integral #Properties; Addition principle, a counting principle in combinatorics; In probability theory, an implication of the additivity axiom, see Probability axioms #Further consequences; Sum rule in quantum mechanics
5+0=5 illustrated with collections of dots. In combinatorics, the addition principle [1] [2] or rule of sum [3] [4] is a basic counting principle.Stated simply, it is the intuitive idea that if we have A number of ways of doing something and B number of ways of doing another thing and we can not do both at the same time, then there are + ways to choose one of the actions.
List of convolutions of probability distributions – the probability measure of the sum of independent random variables is the convolution of their probability measures. Law of total expectation; Law of total variance; Law of total covariance; Law of total cumulance; Taylor expansions for the moments of functions of random variables; Delta method
That is, the probability function f(x) lies between zero and one for every value of x in the sample space Ω, and the sum of f(x) over all values x in the sample space Ω is equal to 1. An event is defined as any subset of the sample space . The probability of the event is defined as
In probability theory, the chain rule [1] (also called the general product rule [2] [3]) describes how to calculate the probability of the intersection of, not necessarily independent, events or the joint distribution of random variables respectively, using conditional probabilities.
The term law of total probability is sometimes taken to mean the law of alternatives, which is a special case of the law of total probability applying to discrete random variables. [ citation needed ] One author uses the terminology of the "Rule of Average Conditional Probabilities", [ 4 ] while another refers to it as the "continuous law of ...