Perbandingan Metode Bootstrap Dan Jackknife Resampling Dalam Menentukan Nilai Estimasi Dan Interval Konfidensi Parameter Regresi - Dessy Ariani; Yuki Novia Nasution; Desi Yuniarti (Program Studi Statistika FMIPA Universitas Mulawarman, 2017)
Regression analysis is a study that describes and evaluates the relationship between an independent variable and the dependent variable for the purpose of estimating or predicting the value of the dependent variable based on the value of the independent variables. Resampling is used when samples obtained for analyzing is less. In this study, Bootstrap method and Jackknife method are using. Both methods are used to find the value of regression parameter estimates and confidence intervals of regression parameter values which applied to the data position of Public Deposits in four groups of banks : Persero Banks, Government Banks, National Private Banks and Foreign Banks to knowing the best resampling methods to find the value of regression parameter estimates and confidence intervals of regression parameter values. There are three independent variables which are used in this study, namely investments loans, working capital loans and consumer loans. From the research results, it is obtained that the Jackknife method is the most appropriate method because it has smaller standard error values so Jackknife methods have a narrow range confidence intervals.