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File:High School Probability and Statistics (Basic).pdf. Size of this JPG preview of this PDF file: 463 × 599 pixels. Other resolutions: 185 × 240 pixels | 371 × 480 pixels | 593 × 768 pixels | 1,275 × 1,650 pixels. This is a file from the Wikimedia Commons. Information from its description page there is shown below.
Probability and statistics are two closely related fields in mathematics, sometimes combined for academic purposes. They are covered in several articles: Probability. Statistics. Glossary of probability and statistics. Notation in probability and statistics. Timeline of probability and statistics. Category:
Probability density functions (pdfs) and probability mass functions are denoted by lowercase letters, e.g. , or . Cumulative distribution functions (cdfs) are denoted by uppercase letters, e.g. , or . In particular, the pdf of the standard normal distribution is denoted by , and its cdf by .
t. e. In probability theory and statistics, a probability distribution is the mathematical function that gives the probabilities of occurrence of possible outcomes for an experiment. [1][2] It is a mathematical description of a random phenomenon in terms of its sample space and the probabilities of events (subsets of the sample space). [3]
Posterior probability is a conditional probability conditioned on randomly observed data. Hence it is a random variable. For a random variable, it is important to summarize its amount of uncertainty. One way to achieve this goal is to provide a credible interval of the posterior probability.
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.
Rayleigh. In probability theory and statistics, the Rayleigh distribution is a continuous probability distribution for nonnegative-valued random variables. Up to rescaling, it coincides with the chi distribution with two degrees of freedom. The distribution is named after Lord Rayleigh (/ ˈreɪli /). [1]
Continuous uniform. In probability theory and statistics, the continuous uniform distributions or rectangular distributions are a family of symmetric probability distributions. Such a distribution describes an experiment where there is an arbitrary outcome that lies between certain bounds. [1]