The IBM SPSS® Bootstrapping module makes bootstrapping, a technique for testing model stability, easier. It estimates sampling distribution of an estimator by resampling with replacement from the original sample. Estimate standard errors and confidence intervals of a population parameter such as a mean, median, proportion, odds ratio, correlation coefficient, regression coefficient or others. Control the numbers of bootstrap samples, set a random number seed and indicate whether a simple or stratified method is appropriate.
This module is included in the SPSS Statistics Base edition for on premises as well as for subscription plans.
Estimate standard errors and confidence intervals
You can estimate standard errors and confidence intervals of a population parameter such as the mean, median, proportion, odds ratio, correlation coefficient, regression coefficient and more.
Test stability of analytical models, procedures across SPSS
Test the stability of analytical models and procedures found throughout the IBM SPSS Statistics product family, including descriptive, means, crosstabs, correlations, regression and many others.
Easily control the number of bootstrap samples
You can modify the number of samples upward or downward. The default setting is 1,000 samples.
Gain a more complete view of your data
Through resampling, SPSS Bootstrapping can create thousands of alternate versions of your data set, providing a more accurate view of what is likely to exist in the population.