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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.
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 ...
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 ...
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 ...
In descriptive statistics, the range of a set of data is size of the narrowest interval which contains all the data. It is calculated as the difference between the largest and smallest values (also known as the sample maximum and minimum ). [1] It is expressed in the same units as the data. The range provides an indication of statistical ...
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Maximum a posteriori (MAP) estimator: for a contrast in the way to calculate estimators when prior knowledge is postulated; Maximum spacing estimation: a related method that is more robust in many situations; Maximum entropy estimation; Method of moments (statistics): another popular method for finding parameters of distributions
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 ...