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  2. Central tendency - Wikipedia

    en.wikipedia.org/wiki/Central_tendency

    The mean (L 2 center) and midrange (L ∞ center) are unique (when they exist), while the median (L 1 center) and mode (L 0 center) are not in general unique. This can be understood in terms of convexity of the associated functions (coercive functions).

  3. Mode (statistics) - Wikipedia

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

    Like the statistical mean and median, the mode is a way of expressing, in a (usually) single number, important information about a random variable or a population. 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.

  4. Binomial distribution - Wikipedia

    en.wikipedia.org/wiki/Binomial_distribution

    In general, there is no single formula to find the median for a binomial distribution, and it may even be non-unique. However, several special results have been established: If np is an integer, then the mean, median, and mode coincide and equal np. [10] [11]

  5. Median - Wikipedia

    en.wikipedia.org/wiki/Median

    Median as a weighted arithmetic mean of all Sample Observations; On-line calculator; Calculating the median; A problem involving the mean, the median, and the mode. Weisstein, Eric W. "Statistical Median". MathWorld. Python script for Median computations and income inequality metrics; Fast Computation of the Median by Successive Binning

  6. 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: ⁡ [] =.

  7. Point estimation - Wikipedia

    en.wikipedia.org/wiki/Point_estimation

    In general, with a normally-distributed sample mean, Ẋ, and with a known value for the standard deviation, σ, a 100(1-α)% confidence interval for the true μ is formed by taking Ẋ ± e, with e = z 1-α/2 (σ/n 1/2), where z 1-α/2 is the 100(1-α/2)% cumulative value of the standard normal curve, and n is the number of data values in that ...

  8. Univariate (statistics) - Wikipedia

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

    The median is a better measure when the data set contains outliers. The mode is simple to locate. One is not restricted to using only one of these measures of central tendency. If the data being analyzed is categorical, then the only measure of central tendency that can be used is the mode.

  9. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    The parameter is the mean or expectation of the distribution (and also its median and mode), while the parameter is the variance. The standard deviation of the distribution is σ {\textstyle \sigma } (sigma).