# Probability

• Basic Probability Formula - Learn how to calculate the probability of an event using the basic probability formula. Understand the concept of favorable and total outcomes.
• Bayes' Theorem Probability - Bayes' Theorem calculator to determine the posterior probability of an event based on prior probabilities and likelihood.
• Bayesian Probability - Bayesian probability formula computes updated probability of a hypothesis based on prior probability and newly acquired evidence or likelihood.
• Bernoulli Distribution Probability - This calculator computes the probability of a specific outcome in a single Bernoulli trial based on the given probability of success.
• Binomial Coefficient - Calculate the binomial coefficient or combinations of selecting k items from a set of n items. Understand the mathematical formula C(n, k) and its use in combinatorics.
• Combinations - Calculate the number of combinations (binomial coefficients) of choosing k items from n options without repetition using this combinations calculator.
• Complementary Probability - Complementary probability refers to the probability that a particular event will not occur. This calculator determines the complement of a given probability.
• Conditional Expectation - Calculate the conditional expectation of a random variable X given the value of another random variable Y using this calculator.
• Conditional Probability - Calculate conditional probability P(A|B) with our easy-to-use tool. Learn how the occurrence of one event affects the probability of another.
• Joint Probability Distribution - Joint probability distribution is a technique used in probability theory to represent the probability of events A and B occurring together.
• Law of Total Probability - Calculate the total probability of an event A using the law of total probability, which relates marginal probabilities to conditional probabilities.
• Marginal Probability Distribution - The marginal probability distribution formula calculates the probability of an event occurring irrespective of the outcome of another random variable.
• Normal Distribution Probability - The normal distribution probability function calculates the probability of a specific value occurring in a normal distribution, given the mean and standard deviation.
• Pascal's Triangle Coefficients - The coefficients in Pascal's triangle are calculated using the formula C(row, col) = row! / (col! * (row - col)!). This calculator helps find the coefficient at a specific position.
• Permutation Formula - The permutation formula calculates the number of ways to arrange a certain number of objects from a set. Learn the formula and its application.
• Probability Density Function with Normal Distribution - The probability density function (PDF) for the normal distribution describes the likelihood of a random variable taking on a certain value within a probability distribution. This calculator helps calculate the PDF for a given value in a normal distribution.
• Probability of Flipping Coin x Times - This calculator helps determine the probability of getting the same outcome when flipping a fair coin a specific number of times.
• Probability of Intersection of Two Events - Learn how to calculate the probability of the intersection of two independent events with this probability calculator.
• Probability of Union of Events - Calculate the probability of the union of two events, A and B, with their probabilities and the probability of their intersection using the formula P(A ∪ B) = P(A) + P(B) - P(A ∩ B).
• Shannon's Information Entropy - Shannon's information entropy quantifies the uncertainty of a random variable by measuring the average rate at which information is produced by a stochastic source of data.
• Cumulative Distribution Function for a Standard Normal Distribution - Calculate the cumulative distribution function (CDF) for a standard normal distribution for any given z-score using this tool. It utilizes the error function for approximation.
• Uniform Distribution Probability - The uniform distribution probability formula calculates the likelihood of a number falling within a specified range, where each outcome is equally likely. Understand its application in statistics.