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  2. Median - Wikipedia

    en.wikipedia.org/wiki/Median

    The median of a normal distribution with mean μ and variance σ 2 is μ. In fact, for a normal distribution, mean = median = mode. The median of a uniform distribution in the interval [a, b] is (a + b) / 2, which is also the mean. The median of a Cauchy distribution with location parameter x 0 and scale parameter y is x 0, the location parameter.

  3. Mode (statistics) - Wikipedia

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

    In a formula, median ≈ (2 × mean + mode)/3. This rule, due to Karl Pearson, often applies to slightly non-symmetric distributions that resemble a normal distribution, but it is not always true and in general the three statistics can appear in any order. [5] [6] For unimodal distributions, the mode is within √ 3 standard deviations of the ...

  4. 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 ( ln ⁡ f ) ′ = 0 {\displaystyle (\ln f)'=0} , we get that:

  5. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    If the mean =, the first factor is 1, and the Fourier transform is, apart from a constant factor, a normal density on the frequency domain, with mean 0 and variance /. In particular, the standard normal distribution φ {\textstyle \varphi } is an eigenfunction of the Fourier transform.

  6. 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]

  7. Median absolute deviation - Wikipedia

    en.wikipedia.org/wiki/Median_absolute_deviation

    The median absolute deviation is a measure of statistical dispersion. Moreover, the MAD is a robust statistic , being more resilient to outliers in a data set than the standard deviation . In the standard deviation, the distances from the mean are squared, so large deviations are weighted more heavily, and thus outliers can heavily influence it.

  8. Majority of U.S. Teens Are Not Drinking, Smoking or Using ...

    www.aol.com/majority-u-teens-not-drinking...

    A national study discovered that teens in the United States consumed significantly less alcohol and drugs in 2024 compared to past years. Teen alcohol use has steadily decreased from 2000 to 2024 ...

  9. Skewness - Wikipedia

    en.wikipedia.org/wiki/Skewness

    In the older notion of nonparametric skew, defined as () /, where is the mean, is the median, and is the standard deviation, the skewness is defined in terms of this relationship: positive/right nonparametric skew means the mean is greater than (to the right of) the median, while negative/left nonparametric skew means the mean is less than (to ...