翻訳と辞書 Words near each other ・ Friedlander–Iwaniec theorem ・ Friedlandpreis der Heimkehrer ・ Friedle Olivier ・ Friedlieb Ferdinand Runge ・ Friedländer ・ Friedländer synthesis ・ Friedman ・ Friedman doctrine ・ Friedman Fleischer & Lowe ・ Friedman Foundation for Educational Choice ・ Friedman Memorial Airport ・ Friedman number ・ Friedman Paul Erhardt ・ Friedman Place ・ Friedman rule ・ Friedman test ・ Friedman translation ・ Friedman Unit ・ Friedman's Inc. ・ Friedman's k-percent rule ・ Friedmann equations ・ Friedmann Nunataks ・ Friedmann Peak ・ Friedmann Valley ・ Friedmann's lark ・ Friedmannia ・ Friedmanniella antarctica ・ Friedmanniella lacustris ・ Friedmanniella lucida ・ Friedmanniella luteola Dictionary Lists mini英和辞書 mini和英辞書 Webster 1913 Latin-English FOLDOC Wikipedia English ウィキペディア

翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Friedman test ： ウィキペディア英語版 Friedman test The Friedman test is a non-parametric statistical test developed by Milton Friedman. Similar to the parametric repeated measures ANOVA, it is used to detect differences in treatments across multiple test attempts. The procedure involves ranking each row (or ''block'') together, then considering the values of ranks by columns. Applicable to complete block designs, it is thus a special case of the Durbin test. Classic examples of use are: * ''n'' wine judges each rate ''k'' different wines. Are any wines ranked consistently higher or lower than the others? * ''n'' wines are each rated by ''k'' different judges. Are the judges' ratings consistent with each other? * ''n'' welders each use ''k'' welding torches, and the ensuing welds were rated on quality. Do any of the torches produce consistently better or worse welds? The Friedman test is used for one-way repeated measures analysis of variance by ranks. In its use of ranks it is similar to the Kruskal–Wallis one-way analysis of variance by ranks. Friedman test is widely supported by many statistical software packages. == Method == #Given data $\backslash \_$, that is, a matrix with $n$ rows (the ''blocks''), $k$ columns (the ''treatments'') and a single observation at the intersection of each block and treatment, calculate the ranks ''within'' each block. If there are tied values, assign to each tied value the average of the ranks that would have been assigned without ties. Replace the data with a new matrix $\backslash \_$ where the entry $r\_$ is the rank of $x\_$ within block $i$. #Find the values: # *$\backslash bar\_\; =\; \backslash frac\; \backslash sum\_^n\; =\; \backslash frac\backslash sum\_^n\; \backslash sum\_^k\; r\_$ # *$SS\_t\; =\; n\backslash sum\_^k\; (\backslash bar\_\; -\; \backslash bar)^2$, # *$SS\_e\; =\; \backslash frac\; \backslash sum\_^n\; \backslash sum\_^k\; (r\_\; -\; \backslash bar)^2$ #The test statistic is given by $Q\; =\; \backslash frac$. Note that the value of Q as computed above does not need to be adjusted for tied values in the data. #Finally, when n or k is large (i.e. n > 15 or k > 4), the probability distribution of Q can be approximated by that of a chi-squared distribution. In this case the p-value is given by $\backslash mathbf(\backslash chi^2\_\; \backslash ge\; Q)$. If n or k is small, the approximation to chi-square becomes poor and the p-value should be obtained from tables of Q specially prepared for the Friedman test. If the p-value is significant, appropriate post-hoc multiple comparisons tests would be performed. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Friedman test」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.