A Study Based on the Application of Bootstrap and Jackknife Methods in Simple Linear Regression Analysis

Tolga Zaman, Kamil Alakuş


In the study, bootstrap and jackknife methods, which are used as a correction term when assumptions of the error in simple linear regressions are not met, are explored in detail. In the application, model parameters, coefficients of determination, standard errors, coefficients of correlation and %95 confidence intervals belonging to these methods are estimated with the help of a real data and the obtained results are interpreted.



Bootstrap; Jackknife; Simple linear regression; Mean squared error; Coefficient of determination; Coefficient of correlation.


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