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Printable version; In other projects ... ≡ 1 × 10 −15 m: ≡ 1 ... foot per second squared: fps 2: ≡ 1 ft/s 2 = 3.048 ...
In forestry, quadratic mean diameter or QMD is a measure of central tendency which is considered more appropriate than arithmetic mean for characterizing the group of trees which have been measured.
1 square yoctometre (ym 2) 1 ym 2 10 −43 100,000 ym 2: 1 femtobarn [3] 10 −42: 1 square zeptometre (zm 2) 1 zm 2 10 −36: 1 square attometre (am 2) 1 am 2 10 −30: 1 square femtometre (fm 2) 1 fm 2 10 −29 66.52 fm 2: Thomson cross-section of the electron [4] 10 −28 100 fm 2: 1 barn, roughly the cross-sectional area of a uranium ...
In examples 1–3, the asymptotic distribution of the statistic is different: in (1) it is normal, in (2) it is chi-squared, and in (3) it is a weighted sum of chi-squared variables. Von Mises' approach is a unifying theory that covers all of the cases above. [ 1 ]
In mathematics and its applications, the mean square is normally defined as the arithmetic mean of the squares of a set of numbers or of a random variable. [ 1 ] It may also be defined as the arithmetic mean of the squares of the deviations between a set of numbers and a reference value (e.g., may be a mean or an assumed mean of the data), [ 2 ...
For example, 1 kilometre is 10 3 (one thousand) times the length of 1 metre, but 1 square kilometre is (10 3) 2 (10 6, one million) times the area of 1 square metre, and 1 cubic kilometre is (10 3) 3 (10 9, one billion) cubic metres.
In probability theory and statistics, the generalized chi-squared distribution (or generalized chi-square distribution) is the distribution of a quadratic form of a multinormal variable (normal vector), or a linear combination of different normal variables and squares of normal variables.
Ordinary least squares regression of Okun's law.Since the regression line does not miss any of the points by very much, the R 2 of the regression is relatively high.. In statistics, the coefficient of determination, denoted R 2 or r 2 and pronounced "R squared", is the proportion of the variation in the dependent variable that is predictable from the independent variable(s).
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