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  2. Interquartile range - Wikipedia

    en.wikipedia.org/wiki/Interquartile_range

    Boxplot (with an interquartile range) and a probability density function (pdf) of a Normal N(0,σ 2) Population. In descriptive statistics, the interquartile range (IQR) is a measure of statistical dispersion, which is the spread of the data. [1] The IQR may also be called the midspread, middle 50%, fourth spread, or H‑spread.

  3. Quantile - Wikipedia

    en.wikipedia.org/wiki/Quantile

    But, in general, the median and the mean can differ. For instance, with a random variable that has an exponential distribution, any particular sample of this random variable will have roughly a 63% chance of being less than the mean. This is because the exponential distribution has a long tail for positive values but is zero for negative numbers.

  4. Quantile function - Wikipedia

    en.wikipedia.org/wiki/Quantile_function

    Because the normal distribution is a location-scale family, its quantile function for arbitrary parameters can be derived from a simple transformation of the quantile function of the standard normal distribution, known as the probit function. Unfortunately, this function has no closed-form representation using basic algebraic functions; as a ...

  5. Quartile - Wikipedia

    en.wikipedia.org/wiki/Quartile

    The Interquartile Range (IQR), defined as the difference between the upper and lower quartiles (), may be used to characterize the data when there may be extremities that skew the data; the interquartile range is a relatively robust statistic (also sometimes called "resistance") compared to the range and standard deviation. There is also a ...

  6. Robust measures of scale - Wikipedia

    en.wikipedia.org/wiki/Robust_measures_of_scale

    One of the most common robust measures of scale is the interquartile range (IQR), the difference between the 75th percentile and the 25th percentile of a sample; this is the 25% trimmed range, an example of an L-estimator. Other trimmed ranges, such as the interdecile range (10% trimmed range) can also be used.

  7. Qualitative variation - Wikipedia

    en.wikipedia.org/wiki/Qualitative_variation

    There are several types of indices used for the analysis of nominal data. Several are standard statistics that are used elsewhere - range, standard deviation, variance, mean deviation, coefficient of variation, median absolute deviation, interquartile range and quartile deviation.

  8. Box plot - Wikipedia

    en.wikipedia.org/wiki/Box_plot

    The third quartile value can be easily obtained by finding the "middle" number between the median and the maximum. For the hourly temperatures, the "middle" number between 70°F and 81°F is 75°F. The interquartile range, or IQR, can be calculated by subtracting the first quartile value (Q 1) from the third quartile value (Q 3):

  9. Quartile coefficient of dispersion - Wikipedia

    en.wikipedia.org/wiki/Quartile_coefficient_of...

    The quartile coefficient of dispersion is the ratio of half of the interquartile range (IQR) to the average of the quartiles (the midhinge): [1] = + = +. Example [ edit ]