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Bootstrapping can be defined as a method to derive robust estimates of all the standard errors as well as the confidence intervals for estimates for example the mean, proportion, median, odds ratio, regression coefficient, correlation coefficient, etc. It can also be considered or utilized to construct hypothesis tests. Bootstrapping can be done with SPSS.
SPSS Bootstrapping can be defined as an efficient technique for ensuring the reliability of the analytical models & also that will generate correct outcomes. It can be used for testing that whether the analytical models as well as procedures, which are found throughout the family of the SPSS Statistics product, are stable or not. The SPSS statistics product family includes correlations, descriptive, crosstabs, means, regression & many others.
Using the SPSS Bootstrapping, the sampling distribution of an estimator can be easily & quickly through re-sampling with substitution from the original sample, thousands of data set alternate versions can be created for more correct view, the impact of outliers as well as anomalies can be reduced which will help for ensuring reliability as well as stability of the models and standard errors as well as confidence intervals of parameter of a population can be estimated for example the mean, proportion, median, correlation coefficient, odds ratio, regression coefficient, etc