Hanifah, Nurul (2016) PENERAPAN METODE WEIGTHED LEAST SQUARE UNTUK MENGATASI HETEROSKEDASTISITAS PADA ANALISIS REGRESI LINEAR. S1 thesis, Universitas Pendidikan Indonesia.
Abstract
Analisis regresi merupakan analisis statistik yang mempalajari bagaimana memodelkan regresi linear. Jika model regresi linear memenuhi uji asumsi klasik dengan metode OLS maka mempunyai sifat BLUE (Beast Linear Unbiased Estimator). Uji heteroskedastisitas,yaitu varian error pada setiap nilai variabel bebas bernilai tidak konstan. Akibat dari heteroskedastisitas yaitu nilai parameter yang diperoleh tetap tidak bias tetapi varian penaksir yang diperoleh menjadi tidak efisien, artinya uji hipotesis yang dilakukan tidak akan memberikan hasil yang baik (tidak valid) atau prediksi koefisien-koefisien populasinya akan keliru. Oleh karena itu untuk mengetahui apakah terdapat heteroskedastisitas dilakukan uji White. Karena terdapat heteroskedastisitas pada skripsi ini, maka harus dilakukan transformasi dengan metode kuadrat trkecil tertimbang (Weighted Least Square).
Kata Kunci: Uji Asumsi Klasik, Weighted least Square, Uji White.
Regression analysis is a statistical analysis that learn how to model linear regression. If a linear regression model meets the Classic Assumption Test by OLS method, it has the nature of BLUE (Best Linear Unbiased Estimator). Error variance at each independent variable value is not constant.
It means that heteroskedasticity test is unfulfilled and the classical assumption is not met.The result of heteroskedastisitas is that the parameter value remains biased but variance estimator becomes inefficient. It means thata hypothesis test
wouldn’t give good results (not valid) or predictions coefficients of the population would be mislead. Therefore, to know whether there are heteroskedasticity, White test is conducted. Because heteroskedasticity exists in this thesis, transformation with weighted least squares method (Weighted Least Square) must be carried out.
Keyword: Classic Assumption Test, Weighted least Square, White Test.
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| Item Type: | Thesis (S1) |
|---|---|
| Additional Information: | No. Panggil: S_MAT_HAN p-2016; Pembimbing : I. Nar Herrhyanto, II. Fitriani Agustina |
| Uncontrolled Keywords: | Uji Asumsi Klasik, Weighted least Square, Uji White. |
| Subjects: | L Education > L Education (General) Q Science > QA Mathematics |
| Divisions: | Fakultas Pendidikan Matematika dan Ilmu Pengetahuan Alam > Program Studi Matematika - S1 |
| Depositing User: | Mr. Cahya Mulyana |
| Date Deposited: | 10 Apr 2017 08:56 |
| Last Modified: | 10 Apr 2017 08:56 |
| URI: | http://repository.upi.edu/id/eprint/23344 |
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