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  2. Mid-range - Wikipedia

    en.wikipedia.org/wiki/Mid-range

    Mid-range. In statistics, the mid-range or mid-extreme is a measure of central tendency of a sample defined as the arithmetic mean of the maximum and minimum values of the data set: [1] The mid-range is closely related to the range, a measure of statistical dispersion defined as the difference between maximum and minimum values.

  3. L-estimator - Wikipedia

    en.wikipedia.org/wiki/L-estimator

    Simple L-estimators can be visually estimated from a box plot, and include interquartile range, midhinge, range, mid-range, and trimean. In statistics, an L-estimator is an estimator which is a linear combination of order statistics of the measurements ( also called an L-statistic ). This can be as little as a single point, as in the median (of ...

  4. Trimmed estimator - Wikipedia

    en.wikipedia.org/wiki/Trimmed_estimator

    Trimmed estimator. In statistics, a trimmed estimator is an estimator derived from another estimator by excluding some of the extreme values, a process called truncation. This is generally done to obtain a more robust statistic, and the extreme values are considered outliers. [1] Trimmed estimators also often have higher efficiency for mixture ...

  5. 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 ...

  6. Midhinge - Wikipedia

    en.wikipedia.org/wiki/Midhinge

    Midhinge. In statistics, the midhinge is the average of the first and third quartiles and is thus a measure of location . Equivalently, it is the 25% trimmed mid-range or 25% midsummary; it is an L-estimator . The midhinge is related to the interquartile range (IQR), the difference of the third and first quartiles (i.e. ), which is a measure of ...

  7. Maximum likelihood estimation - Wikipedia

    en.wikipedia.org/wiki/Maximum_likelihood_estimation

    In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of an assumed probability distribution, given some observed data.This is achieved by maximizing a likelihood function so that, under the assumed statistical model, the observed data is most probable.

  8. Likelihood function - Wikipedia

    en.wikipedia.org/wiki/Likelihood_function

    v. t. e. The likelihood function (often simply called the likelihood) is the joint probability mass (or probability density) of observed data viewed as a function of the parameters of a statistical model. [1] [2] [3] Intuitively, the likelihood function is the probability of observing data assuming is the actual parameter.

  9. Interquartile mean - Wikipedia

    en.wikipedia.org/wiki/Interquartile_mean

    Interquartile mean. The interquartile mean ( IQM) (or midmean) is a statistical measure of central tendency based on the truncated mean of the interquartile range. The IQM is very similar to the scoring method used in sports that are evaluated by a panel of judges: discard the lowest and the highest scores; calculate the mean value of the ...