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Fisher's z-distribution is the statistical distribution of half the logarithm of an F distribution variate:
It is a formula that can be used to transform the values of r(corelation coefficient) to make them to align more closely to the normal distribution.
It was first described by Ronald Fisher in a paper delivered at the International Mathematical Congress of 1924 in Toronto, entitled "On a distribution yielding the error functions of several well-known statistics" (Proceedings of the International Congress of Mathematics, Toronto, 2: 805-813 (1924). Nowadays one usually uses the F distribution instead.
See also[]
- z-score a different concept
References[]
- Fisher, R.A. (1924) On a Distribution Yielding the Error Functions of Several Well Known Statistics Proceedings of the International Congress of Mathematics, Toronto, 2: 805-813 pdf copy
External links[]
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Probability distributions [[[:Template:Tnavbar-plain-nodiv]]] | |
|---|---|---|
| Univariate | Multivariate | |
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| Continuous: | Beta • Beta prime • Cauchy • chi-square • Dirac delta function • Erlang • exponential • exponential power • F • fading • Fisher's z • Fisher-Tippett • Gamma • generalized extreme value • generalized hyperbolic • generalized inverse Gaussian • Hotelling's T-square • hyperbolic secant • hyper-exponential • hypoexponential • inverse chi-square • inverse gaussian • inverse gamma • Kumaraswamy • Landau • Laplace • Lévy • Lévy skew alpha-stable • logistic • log-normal • Maxwell-Boltzmann • Maxwell speed • normal (Gaussian) • Pareto • Pearson • polar • raised cosine • Rayleigh • relativistic Breit-Wigner • Rice • Student's t • triangular • type-1 Gumbel • type-2 Gumbel • uniform • Voigt • von Mises • Weibull • Wigner semicircle | Dirichlet • Kent • matrix normal • multivariate normal • von Mises-Fisher • Wigner quasi • Wishart |
| Miscellaneous: | Cantor • conditional • exponential family • infinitely divisible • location-scale family • marginal • maximum entropy • phase-type • posterior • prior • quasi • sampling | |
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