Analisis varian: Béda antarrépisi

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Révisi nurutkeun 6 Séptémber 2004 03.26

Dina statistik, analisa varian (ANOVA) nyaeta kumpulan model statistis sarta prosedur nu pakait nu ngabandingan mean ku nukerkeun sakabeh varian observasi kana sababaraha bagian. Teknik analisa varian mimiti diwanohkeun ku statistikawan jeung ahli genetik Ronald Fisher dina taun 1920-an sarta 1930-an. Aya tilu kelas konsep model nyaeta:

Model efek-fixed nu nganggap yen data asalna tina populasi normal nu mibanda nilai mean beda.

Model efek-random nu nganggap yen data dijelaskeun sacara hirarki ku bedana populasi nu beda dina konstrain hirarki.

Model campuran nu ngajelaskeun kaayan boh efek fixed atawa random aya.

Teknik dasarna nyaeta ngabagi total jumlah kuadrat kana sababaraha komopen pakait kana efek dina model. Contona, rek nembongkeun ANOVA sederhana ku make hiji perlakuan dina tingkat nu beda. (Lamun tingkat perlakuan bisa diitung sarta efekna linier, analisa régrési liniér bisa dipake).

SS_{\hbox{Total}}=SS_{\hbox{Error}}+SS_{\hbox{Treatments}}

Jumlah tingkat kabebasan (disingkat df) bisa dibagi-bagi ku cara nu sarua sarta hususna dina sebaran Chi-kuadrat nu ngajelaskeun hubungan jumlah kuadrat.

df_{\hbox{Total}}=df_{\hbox{Error}}+df_{\hbox{Treatments}}

Model fixed-efek

Model fixed-efek analisa varian dipake keur kaayaan dimana nu ngagawekeun percobaan ngabogaan sababaraha perlakuan dina percobaanna, unggal percobaan ngan mangaruhan kana mean sebaran normal tina variabel nu mangaruhan tadi.

Model efek-random

Model efek-random dipake keur ngajelaskeun kaayaan beda nu teu bisa dibandingkeun dina percobaan. Conto sederhana nyaeta estimasi mean teu dipikanyaho numana individu kabehanna beda. Dina kasus ieu, variasi antara individu ngabingungkeun kana alat observasi.

Tingkat kabebasan

Tingkat kabebasan nunjukeun wilangan observasi efektip nu mere pangaruh kana jumlah kuadrat dina ANOVA, jumlah total observasi dikurangan ku jumlah konstrain linier dina data.

Tes kapercayaan

Analisa varian nuju kana tes kapercayaan statistik make sebaran-F Fisher.

Tempo oge: ANCOVA MANOVA

@@ Baris ka-1: / Baris ka-1: @@
-Dina [[statistik]], '''analysis of variance''' ('''ANOVA''') is a collection of [[statistical model]]s and their associated procedures which compare means by splitting the overall observed variance into different parts.  The initial techniques of the analysis of variance were pioneered by the [[statistician]] and [[geneticist]] [[Ronald Fisher]] in the [[1920s]] and [[1930s]].  There are three conceptual classes of such models:
+Dina [[statistik]], '''analisa varian''' ('''ANOVA''') nyaeta kumpulan [[statistical model|model statistis]] sarta prosedur nu pakait nu ngabandingan mean ku nukerkeun sakabeh varian observasi kana sababaraha bagian. Teknik analisa varian mimiti diwanohkeun ku [[statistician|statistikawan]] jeung [[geneticist|ahli genetik]] [[Ronald Fisher]] dina taun [[1920]]-an sarta [[1930]]-an.  Aya tilu kelas konsep model nyaeta:
-*Fixed-effects model assumes that the data come from [[normal distribution|normal populations]] which differ in their means.
+*Model efek-fixed nu nganggap yen data asalna tina [[sebaran normal|populasi normal]] nu mibanda nilai mean beda.
+*Model efek-random nu nganggap yen data dijelaskeun sacara hirarki ku bedana populasi nu beda dina konstrain hirarki.
-*Random-effects models assume that the data describe a hierarchy of different populations whose differences are constrained by the hierarchy.
-*Mixed models describe situations where both fixed and random effects are present.
+*Model campuran nu ngajelaskeun kaayan boh efek fixed atawa random aya.
+Teknik dasarna nyaeta ngabagi total jumlah kuadrat kana sababaraha komopen pakait kana efek dina model. Contona, rek nembongkeun ANOVA sederhana ku make hiji ''perlakuan'' dina tingkat nu beda. (Lamun tingkat perlakuan bisa diitung sarta efekna linier, analisa [[régrési liniér]] bisa dipake).
-The fundamental technique is a partitioning of the total sum of squares into components related to the effects in the model used. For example, we show the model for a simplified ANOVA with one type of treatment at different levels. (If the treatment levels are quantitative and the effects are linear, a [[régrési liniér]] analysis may be appropriate.)
 : <math>SS_{\hbox{Total}} = SS_{\hbox{Error}} + SS_{\hbox{Treatments}}</math>
-The number of degrees of freedom (abbreviated ''df'') can be partitioned in a similar way and specifies the [[sebaran Chi-kuadrat]] which describes the associated sums of squares.
+Jumlah tingkat kabebasan (disingkat ''df'') bisa dibagi-bagi ku cara nu sarua sarta hususna dina [[sebaran Chi-kuadrat]] nu ngajelaskeun hubungan jumlah kuadrat.
 : <math>df_{\hbox{Total}} = df_{\hbox{Error}} + df_{\hbox{Treatments}}</math>
-== Fixed-effects model ==
+== Model fixed-efek ==
+Model fixed-efek analisa varian dipake keur kaayaan dimana nu ngagawekeun percobaan ngabogaan sababaraha perlakuan dina percobaanna, unggal percobaan ngan mangaruhan kana mean sebaran normal tina ''variabel nu mangaruhan'' tadi.
-The fixed-effects model of analysis of variance applies to situations in which the experimenter has subjected his experimental material to several treatments, each of which affects only the mean of the underlying normal distribution of the ''response variable''.
 == Model efek-random ==