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Bootstrapping
Bootstrapping
The IBM® SPSS® Bootstrapping module makes bootstrapping, a technique for testing model stability, simpler for you to use:
- Estimates the sampling distribution of an estimator by resampling with replacement from your original sample.
- Estimates standard errors and confidence intervals for a population parameter such as the mean, median, proportion, odds ratio, correlation coefficient, regression coefficient and more.
- Controls the number of bootstrap samples, sets a random number seed and indicates whether a simple or stratified method is appropriate.
This module is available in the IBM® SPSS® Statistics Base edition for traditional license use and as part of the base for monthly or annual subscriptions.
Visit the IBM SPSS Statistics Gradpack page to explore all the options available for students and teachers.
Feature spotlights
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 the stability of analytical models and procedures found throughout the IBM SPSS Statistics product family, including descriptive, means, crosstabs, correlations, regression and many others.
You can modify the number of samples upward or downward. The default setting is 1,000 samples.
Through resampling, SPSS Bootstrapping can create thousands of alternate versions of your data set to provide a more accurate view of what is likely to exist in the population.
Technical details
- For on-premises and subscription plans: purchase the Base edition.
- Processor: 2 GHz or faster
- Display: 1024*768 or higher
- Memory: 4 GB of RAM required, 8 GB of RAM or more recommended
- Disk space: 2 GB or more