費雪變換(英語:Fisher transformation)是統計學中用於相關係數假設檢驗的一種方法。對樣本相關係數進行費雪變換後,可以用來檢驗關於總體相關係數ρ的假設。[1][2] 費雪變換 定義 已知N組雙變量樣本(Xi, Yi), i = 1, ..., N,樣本相關係數r為 r = ∑ i = 1 N ( X i − X ¯ ) ( Y i − Y ¯ ) ∑ i = 1 N ( X i − X ¯ ) 2 ∑ i = 1 N ( Y i − Y ¯ ) 2 {\displaystyle r={\frac {\sum _{i=1}^{N}(X_{i}-{\bar {X}})(Y_{i}-{\bar {Y}})}{{\sqrt {\sum _{i=1}^{N}(X_{i}-{\bar {X}})^{2}}}{\sqrt {\sum _{i=1}^{N}(Y_{i}-{\bar {Y}})^{2}}}}}} 於是,r的費雪變換可定義為 z := 1 2 ln ( 1 + r 1 − r ) = arctanh ( r ) . {\displaystyle z:={1 \over 2}\ln \left({1+r \over 1-r}\right)=\operatorname {arctanh} (r).} 當(X, Y)為二元正態分布且(Xi, Yi)對相互獨立時,z近似為正態分布。其均值為 1 2 ln ( 1 + ρ 1 − ρ ) , {\displaystyle {1 \over 2}\ln \left({{1+\rho } \over {1-\rho }}\right),} 標準差為 1 N − 3 , {\displaystyle {1 \over {\sqrt {N-3}}},} 其中N是樣本大小,ρ是變量X與Y的總體相關係數。 費雪變換及其逆變換 r = exp ( 2 z ) − 1 exp ( 2 z ) + 1 = tanh ( z ) , {\displaystyle r={{\exp(2z)-1} \over {\exp(2z)+1}}=\operatorname {tanh} (z),} 可以用於構造ρ的置信區間。 參考文獻 [1]Fisher, R.A. Frequency distribution of the values of the correlation coefficient in samples of an indefinitely large population. Biometrika (Biometrika Trust). 1915, 10 (4): 507–521. JSTOR 2331838. doi:10.2307/2331838. [2]Fisher, R.A. On the `probable error' of a coefficient of correlation deduced from a small sample (PDF). Metron. 1921, 1: 3–32 [2015-09-03]. (原始內容存檔 (PDF)於2021-02-12). Wikiwand - on Seamless Wikipedia browsing. On steroids.