The Stratified Sample Transformation wizard creates a stratified sample of a table or view; the sample can be either a table or a view. You can specify the sample size either as a number of records or as a percentage of records. You can also specify a random seed.
In a stratified sample, the population is divided into separate groups according to values of an attribute; each group is randomly sampled separately. For example, you might have an attribute SEX with two values "Male" and "Female"; a stratified sample would be a random sample of all cases where SEX="Male" combined with a random sample of all cases where SEX="Female". In the sample, the two groups will have approximately the same number of members.
Stratified sampling is useful when the values of the attributes are skewed. For example, suppose that 99% of the cases in the example of the previous paragraph have SEX="Female".
You could use stratified sampling to create a new data set where the number of cases with SEX="Female" is approximately the same as the number of cases with SEX="Male".
For more information, see How to Use Stratified Sampling.
The output of the wizard is described in Output.
After the wizard creates the new table or view, it displays the new table or view.
If you do not want to see this page the next time that you launch the wizard, uncheck the Show this page next time box.
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