TRANSFORMASI BOX-COX PADA ANALISIS REGRESI LINIER SEDERHANA

Authors

  • Elvi Yati
  • Dodi Devianto
  • Yudiantri Asdi

DOI:

https://doi.org/10.25077/jmu.2.2.115-122.2013

Abstract

Asumsi dasar regresi merupakan asumsi yang harus dipenuhi dalam memod-
elkan hubungan antara variabel tak bebas (Y ) dengan variabel bebas (X) dalam analisis
regresi linier sederhana. Jika asumsi tersebut tidak dipenuhi, maka dapat dilakukan
transformasi Box-Cox terhadap variabel tak bebas, dimana Y dipangkatkan dengan ,
sehingga menjadi Y . Pendugaan parameter dilakukan dengan Metode Kemungkinan
Maksimum dimana dipilih yang memiliki jumlah kuadrat sisaan paling kecil. Param-
eter tersebut digunakan dalam transformasi sehingga diperoleh data yang memenuhi
asumsi normalitas, homogenitas, dan linieritas.

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Published

10-06-2013

Issue

Vol. 2 No. 2 (2013)

Section

Articles

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