Summarize IBM SPSS Statistics data in different
styles for different audiences


IBM SPSS Custom Tables enables you to summarize SPSS Statistics data, and display your analyses as presentation-quality, production-ready tables. It provides analytical capabilities to help you learn from your data, and offers advanced features that allow you to build tables people can easily read and interpret. You can work with output and present survey results by using nesting, stacking and multiple response categories, and handle missing values and change labels and formats.

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Use in-depth analyses

Run Chi-square, column proportions and column means tests, and add more insight to tables by identifying differences, changes or trends in your data.

Preview tables as you build them

View your tables as you select variables and table options to get the output you want.

Customize layout and format

Exclude specific categories, display missing value cells and add subtotals to your tables to communicate results clearly.


Explore detailed information about this product, its uses and how it can help your business.

See how it works

See specialized features designed to support a range of custom reporting needs.

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Solve research and business problems through data analysis

Read how SPSS Statistics helps you access and manage data, perform analysis, and share results to improve decisions.

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Features spotlight

  • Drag-and-drop table builder interface
  • Provides more than 160 summary statistics
  • Nest variables to any level, and cross-tabulate multiple independent variables in the same table
  • Display multiple statistics in rows, columns or layers, and show significance test results directly


Improve the accuracy of predictions with advanced regression procedures

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Streamlines the data preparation process so that you can get ready for analysis faster and reach more accurate conclusions

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Quickly develop reliable forecasts and predict trends using time-series data

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Estimate the sampling distribution of an estimator by resampling with replacement from the original sample

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