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  2. List of probability distributions - Wikipedia

    en.wikipedia.org/wiki/List_of_probability...

    It represents a discrete probability distribution concentrated at 0 — a degenerate distribution — it is a Distribution (mathematics) in the generalized function sense; but the notation treats it as if it were a continuous distribution. The Kent distribution on the two-dimensional sphere.

  3. Biostatistics - Wikipedia

    en.wikipedia.org/wiki/Biostatistics

    Biostatistics (also known as biometry) is a branch of statistics that applies statistical methods to a wide range of topics in biology. It encompasses the design of biological experiments , the collection and analysis of data from those experiments and the interpretation of the results.

  4. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    Many test statistics, scores, and estimators encountered in practice contain sums of certain random variables in them, and even more estimators can be represented as sums of random variables through the use of influence functions. The central limit theorem implies that those statistical parameters will have asymptotically normal distributions.

  5. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    A discrete probability distribution is applicable to the scenarios where the set of possible outcomes is discrete (e.g. a coin toss, a roll of a die) and the probabilities are encoded by a discrete list of the probabilities of the outcomes; in this case the discrete probability distribution is known as probability mass function.

  6. Quizlet - Wikipedia

    en.wikipedia.org/wiki/Quizlet

    Quizlet's primary products include digital flash cards, matching games, practice electronic assessments, and live quizzes. In 2017, 1 in 2 high school students used Quizlet. [ 4 ] As of December 2021, Quizlet has over 500 million user-generated flashcard sets and more than 60 million active users.

  7. Random variable - Wikipedia

    en.wikipedia.org/wiki/Random_variable

    A mixed random variable is a random variable whose cumulative distribution function is neither discrete nor everywhere-continuous. [10] It can be realized as a mixture of a discrete random variable and a continuous random variable; in which case the CDF will be the weighted average of the CDFs of the component variables. [10]

  8. Continuous or discrete variable - Wikipedia

    en.wikipedia.org/wiki/Continuous_or_discrete...

    In probability theory and statistics, the probability distribution of a mixed random variable consists of both discrete and continuous components. A mixed random variable does not have a cumulative distribution function that is discrete or everywhere-continuous. An example of a mixed type random variable is the probability of wait time in a queue.

  9. Statistical model - Wikipedia

    en.wikipedia.org/wiki/Statistical_model

    In Bayesian statistics, the model is extended by adding a probability distribution over the parameter space . A statistical model can sometimes distinguish two sets of probability distributions. The first set Q = { F θ : θ ∈ Θ } {\displaystyle {\mathcal {Q}}=\{F_{\theta }:\theta \in \Theta \}} is the set of models considered for inference.