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Directional statistics (also circular statistics or spherical statistics) is the subdiscipline of statistics that deals with directions (unit vectors in Euclidean space, R n), axes (lines through the origin in R n) or rotations in R n. More generally, directional statistics deals with observations on compact Riemannian manifolds including the ...
a test for periodicity in irregularly sampled data, [1] a derivation of the above to test for non-uniformity (as unimodal clustering) of a set of points on a circle (e.g. compass directions), [ 2 ] sometimes known as the Rayleigh z test.
In probability theory and directional statistics, the von Mises distribution (also known as the circular normal distribution or the Tikhonov distribution) is a continuous probability distribution on the circle. It is a close approximation to the wrapped normal distribution, which is the circular analogue of the normal distribution.
Raleigh plots was first introduced by Lord Rayleigh.The concept of Raleigh plots evolved from Raleigh tests, also introduced by Lord Rayleigh in 1880. The Rayleigh test is a popular statistical test used to measure the concentration of data points around a circle, identifying any unimodal bias in the distribution. [5]
The circular standard deviation, which is a useful measure of dispersion for the wrapped normal distribution and its close relative, the von Mises distribution is given by: s = ln ( R − 2 ) 1 / 2 = σ {\displaystyle s=\ln(R^{-2})^{1/2}=\sigma }
In mathematics and statistics, a circular mean or angular mean is a mean designed for angles and similar cyclic quantities, such as times of day, and fractional parts of real numbers. This is necessary since most of the usual means may not be appropriate on angle-like quantities.
In probability and statistics, a circular distribution or polar distribution is a probability distribution of a random variable whose values are angles, usually taken to be in the range [0, 2π). [1] A circular distribution is often a continuous probability distribution , and hence has a probability density , but such distributions can also be ...
Directional statistics is the subdiscipline of statistics that deals with directions (unit vectors in R n), axes (lines through the origin in R n) or rotations in R n. The means and variances of directional quantities are all finite, so that the central limit theorem may be applied to the particular case of directional statistics. [2]