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  2. Mode (statistics) - Wikipedia

    en.wikipedia.org/wiki/Mode_(statistics)

    The numerical value of the mode is the same as that of the mean and median in a normal distribution, and it may be very different in highly skewed distributions. The mode is not necessarily unique in a given discrete distribution since the probability mass function may take the same maximum value at several points x 1, x 2, etc.

  3. List of probability distributions - Wikipedia

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

    The Beta distribution on [0,1], a family of two-parameter distributions with one mode, of which the uniform distribution is a special case, and which is useful in estimating success probabilities. The four-parameter Beta distribution, a straight-forward generalization of the Beta distribution to arbitrary bounded intervals [,].

  4. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    Mode: for a discrete ... A discrete probability distribution is the probability distribution of a random variable that can take on only a countable number of values ...

  5. Multimodal distribution - Wikipedia

    en.wikipedia.org/wiki/Multimodal_distribution

    In statistics, a multimodal distribution is a probability distribution with more than one mode (i.e., more than one local peak of the distribution). These appear as distinct peaks (local maxima) in the probability density function, as shown in Figures 1 and 2. Categorical, continuous, and discrete data can all form multimodal distributions.

  6. Triangular distribution - Wikipedia

    en.wikipedia.org/wiki/Triangular_distribution

    This distribution for a = 0, b = 1 and c = 0.5—the mode (i.e., the peak) is exactly in the middle of the interval—corresponds to the distribution of the mean of two standard uniform variables, that is, the distribution of X = (X 1 + X 2) / 2, where X 1, X 2 are two independent random variables with standard uniform distribution in [0, 1]. [1]

  7. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    In probability theory and statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable. The general form of its probability density function is [ 2 ] [ 3 ] f ( x ) = 1 2 π σ 2 e − ( x − μ ) 2 2 σ 2 . {\displaystyle f(x)={\frac {1}{\sqrt {2\pi \sigma ^{2 ...

  8. Central tendency - Wikipedia

    en.wikipedia.org/wiki/Central_tendency

    In statistics, a central tendency (or measure of central tendency) is a central or typical value for a probability distribution. [ 1 ] Colloquially, measures of central tendency are often called averages .

  9. Dirichlet distribution - Wikipedia

    en.wikipedia.org/wiki/Dirichlet_distribution

    The Dirichlet distribution is the conjugate prior distribution of the categorical distribution (a generic discrete probability distribution with a given number of possible outcomes) and multinomial distribution (the distribution over observed counts of each possible category in a set of categorically distributed observations).