What it can do for your business
This 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.
Bootstrapping is included in the Premium package, and is available at an additional cost for the Base, Standard and Professional packages.
Quickly and easily estimate the sampling distribution of an estimator by resampling with replacement from the original sample.
Create thousands of alternate versions of a data set for a more accurate view of what is likely to exist in the population.
Ensure stability, reliability of models
Mitigate outliers and anomalies that can degrade the accuracy or applicability of your analysis. Gain a more comprehensive view of data for creating models.
- Estimate standard errors and confidence intervals
- Test stability of analytical models, procedures across SPSS
- Easily control the number of bootstrap samples
- Gain a more complete view of your data
- See all Module features in license versions
- Compare different SPSS Statistics packages