METODE WHITEUNTUK HETEROSCEDASTICITY-CORRECTED STANDARD ERRORS TERHADAP REGRESI LINEAR

Anggar Dwi Julianto, NIM.: 15610036 (2022) METODE WHITEUNTUK HETEROSCEDASTICITY-CORRECTED STANDARD ERRORS TERHADAP REGRESI LINEAR. Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

Preview	Text (METODE WHITEUNTUK HETEROSCEDASTICITY-CORRECTED STANDARD ERRORS TERHADAP REGRESI LINEAR) 15610036_BAB-I_IV-atau-V_DAFTAR-PUSTAKA.pdf - Published Version Download (2MB) | Preview
	Text (METODE WHITEUNTUK HETEROSCEDASTICITY-CORRECTED STANDARD ERRORS TERHADAP REGRESI LINEAR) 15610036_BAB-II_sampai_SEBELUM-BAB-TERAKHIR.pdf - Published Version Restricted to Registered users only Download (3MB) | Request a copy

Abstract

Regression analysis is a statistical technique to create an equation that connects the dependent variable with the independent variable. By knowing the existence of a relationship between variables, it can be estimated a variable based on other variables through the equations made on the relationship. Multiple linear regression analysis has several classical assumptions that must be met in order to obtain a model estimator with the Best Linear Unbiased Estimator (BLUE) trait. One of the classic assumptions that is often not fulfilled is the assumption of homoscedasticity. Deviations from the assumption of homoscedasticity are called heteroscedasticity. One way to deal with heteroscedasticity problems is using the White method. The White method is one of the alternatives for dealing with the heteroscedasticity problem. White’s method is more sensitive in dealing with heteroscedasticity when there is a linear rather than quadratic relationship between the error and the independent variable.

Share this knowledge with your friends :

Actions (login required)

View Item