Réliabilitas (statistika): Béda antarrépisi

Konten dihapus Konten ditambahkan
Ilhambot (obrolan | kontribusi)
m Ngarapihkeun éjahan, replaced: beda → béda (2)
Ilhambot (obrolan | kontribusi)
m Ngarapihkeun éjahan, replaced: Metoda → métodeu (5), hade → hadé
Baris ka-1:
Dina [[statistika]], '''réliabilitas''' hartina runtuyan ukuran nu angger atawa alat keur ngukur. Réliabilitas henteu pakait langsung jeung [[validitas (psikométri)|validitas]]. Réliabilitas nyaéta ukuran nu bisa dipercaya keur ngukur sacara angger, tapi teu perlu kana naon anu diukur. Conto, sanajan loba tes anu bisa diandelkeun, tapi teu sakabéh tes nembongkeun hasil nu hadehadé keur ngagambarkeun hij pagawaéan.
 
Dina elmu [[experiment|percobaan]], '''reliabilitas''' nyaéta ukuran tes nu masih keneh angger sanggeus tes dipigawe sababaraha kali kana subyek nu sarua dina kaayan nu ampir sarua oge. Hij percobaan bisa diandelkeun lamun hasilna angger dina unggal ukuran, sarta teu bisa diandelkeun lamun hasilna béda.
Baris ka-5:
== Estimasi ==
 
Reliabilitas bisa diestimasi ku sababaraha cara nu bisa dikelompokkeun kana dua tipe nyaéta: administrasi-tunggal jeung administrasi-multiple. Metodamétodeu administrasi-multiple merlukeun dua peniley dina administrasina. Dina metodamétodeu ''test-retest'', reliabiliti dianggap minangka ''[[Pearson product-moment correlation coefficient]]'' antara dua ukuran administrasi nu sarua. Dina metodamétodeu ''alternate forms'', reliabiliti diitung maké ''Pearson product-moment correlation coefficient'' tina dua bentuk nu béda, ilaharna di-administrasi-keun babarengan. Metodamétodeu administrasi-tunggal kaasup ''split-half'' sarta ''internal consistency''. Metodamétodeu ''split-half'' ngawengku ukuran dua ''halves'' minangka bentuk alternatipna. Ieu estimasi "halves reliability" saterusna dilajuning lakukeun ku cara maké ''[[Spearman-Brown prediction formula]]''. Ukuran internal nu ilahar dipaké nyaéta [[Cronbach's alpha]], nu ilaharna dianggap minangka [[mean]] keur sakabéh koefisien ''split-half''.
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Each of these estimation methods is sensitive to different sources of error and so might not be expected to be equal. Also, reliability is a property of the ''scores of a measure'' rather than the measure itself and are thus said to be ''sample dependent''. Reliability estimates from one sample might differ from those of a second sample (beyond what might be expected due to sampling variations) if the second sample is drawn from a different population because the true reliability is different in this second population. (This is true of measures of all types--yardsticks might measure houses well yet have poor reliability when used to measure the lengths of insects.)