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  2. Mode (statistics) - Wikipedia

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

    Mode (statistics) In statistics, the mode is the value that appears most often in a set of data values. [1] If X is a discrete random variable, the mode is the value x at which the probability mass function takes its maximum value (i.e., x=argmaxxi P (X = xi)). In other words, it is the value that is most likely to be sampled.

  3. Log-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Log-normal_distribution

    Comparison of mean, median and mode of two log-normal distributions with different skewness. The mode is the point of global maximum of the probability density function. In particular, by solving the equation (⁡) ′ =, we get that:

  4. Median - Wikipedia

    en.wikipedia.org/wiki/Median

    Median. Calculating the median in data sets of odd (above) and even (below) observations. The median of a set of numbers is the value separating the higher half from the lower half of a data sample, a population, or a probability distribution. For a data set, it may be thought of as the “middle" value. The basic feature of the median in ...

  5. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    A normal distribution or Gaussian distribution (also known as the "bell-shaped curve") is a concept used in probability theory and statistics. [ 2 ] The normal distribution concept is applied in numerous disciplines, including education, psychology, economics, business, the sciences and nursing.

  6. Weibull distribution - Wikipedia

    en.wikipedia.org/wiki/Weibull_distribution

    In probability theory and statistics, the Weibull distribution / ˈwaɪbʊl / is a continuous probability distribution. It models a broad range of random variables, largely in the nature of a time to failure or time between events. Examples are maximum one-day rainfalls and the time a user spends on a web page.

  7. Central tendency - Wikipedia

    en.wikipedia.org/wiki/Central_tendency

    The following may be applied to one-dimensional data. Depending on the circumstances, it may be appropriate to transform the data before calculating a central tendency. Examples are squaring the values or taking logarithms. Whether a transformation is appropriate and what it should be, depend heavily on the data being analyzed.

  8. Average absolute deviation - Wikipedia

    en.wikipedia.org/wiki/Average_absolute_deviation

    Average absolute deviation. The average absolute deviation (AAD) of a data set is the average of the absolute deviations from a central point. It is a summary statistic of statistical dispersion or variability. In the general form, the central point can be a mean, median, mode, or the result of any other measure of central tendency or any ...

  9. Probability density function - Wikipedia

    en.wikipedia.org/wiki/Probability_density_function

    Probability density function. Box plot and probability density function of a normal distribution N(0, σ2). Geometric visualisation of the mode, median and mean of an arbitrary unimodal probability density function. [1] In probability theory, a probability density function (PDF), density function, or density of an absolutely continuous random ...