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词汇 binomial distribution
释义

Definition of binomial distribution in English:

binomial distribution

noun
Statistics
  • A frequency distribution of the possible number of successful outcomes in a given number of trials in each of which there is the same probability of success.

    〔统计〕二项分布

    Example sentencesExamples
    • Then Y follows a binomial distribution with number of trials n and probability of success P = C (here expressed as a decimal between 0 and 1).
    • As and get larger, the distribution becomes closer to a Gaussian, although it is always flatter than the binomial distribution with success probability and independent outcomes.
    • Such a ‘rate’ can be modeled statistically by the probability parameter of a binomial distribution.
    • Full-sib family sizes in a sample are assumed to follow either a Poisson distribution with parameter or a negative binomial distribution with parameters (probability of success) and (number of successes).
    • The random component of our generalized linear model is the binomial distribution with probability of success equal to [theta].

Definition of binomial distribution in US English:

binomial distribution

noun
Statistics
  • A frequency distribution of the possible number of successful outcomes in a given number of trials in each of which there is the same probability of success.

    〔统计〕二项分布

    Example sentencesExamples
    • The random component of our generalized linear model is the binomial distribution with probability of success equal to [theta].
    • Then Y follows a binomial distribution with number of trials n and probability of success P = C (here expressed as a decimal between 0 and 1).
    • Full-sib family sizes in a sample are assumed to follow either a Poisson distribution with parameter or a negative binomial distribution with parameters (probability of success) and (number of successes).
    • Such a ‘rate’ can be modeled statistically by the probability parameter of a binomial distribution.
    • As and get larger, the distribution becomes closer to a Gaussian, although it is always flatter than the binomial distribution with success probability and independent outcomes.
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