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  2. Mid-range - Wikipedia

    en.wikipedia.org/wiki/Mid-range

    For n = 1 or 2, the midrange and the mean are equal (and coincide with the median), and are most efficient for all distributions. For n = 3, the modified mean is the median, and instead the mean is the most efficient measure of central tendency for values of γ 2 from 2.0 to 6.0 as well as from −0.8 to 2.0.

  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 (or L-statistic) is an estimator which is a linear combination of order statistics of the measurements.

  4. Midhinge - Wikipedia

    en.wikipedia.org/wiki/Midhinge

    The two are complementary in sense that if one knows the midhinge and the IQR, one can find the first and third quartiles. The use of the term "hinge" for the lower or upper quartiles derives from John Tukey 's work on exploratory data analysis in the late 1970s, [ 1 ] and "midhinge" is a fairly modern term dating from around that time.

  5. Central tendency - Wikipedia

    en.wikipedia.org/wiki/Central_tendency

    Thus standard deviation about the mean is lower than standard deviation about any other point, and the maximum deviation about the midrange is lower than the maximum deviation about any other point. The 1-norm is not strictly convex, whereas strict convexity is needed to ensure uniqueness of the minimizer. Correspondingly, the median (in this ...

  6. Fact or Fiction: Something is seriously wrong with the NBA - AOL

    www.aol.com/sports/fact-fiction-something...

    Everything but midrange jumpers is up, including dunks. Over a 20-year period from the turn of the century to the current era, dunks increased by 35%, according to RunRepeat.com.

  7. Range (statistics) - Wikipedia

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

    For n independent and identically distributed discrete random variables X 1, X 2, ..., X n with cumulative distribution function G(x) and probability mass function g(x) the range of the X i is the range of a sample of size n from a population with distribution function G(x).

  8. How to retire on less than $1 million and never run out of money

    www.aol.com/finance/retire-less-1-million-never...

    Bottom line. Ultimately, whether you can retire on less than $1 million will largely depend on your spending needs during retirement and your remaining life expectancy.

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