SPSS Statistics 184.108.40.206
Statistical analysis software platform
|Minimum OS:||macOS 10.12.0|
Version History 220.127.116.11
You can find release notes for this version here: [community.ibm.com]
IBM SPSS Statistics
Uncover data insights that can help solve business and research problems
Why IBM SPSS Statistics?
IBM SPSS Statistics is a powerful statistical software platform. It delivers a robust set of features that lets your organization extract actionable insights from its data.
• With SPSS Statistics you can:
• Analyze and better understand your data, and solve complex business and research problems through a user friendly interface.
• More quickly understand large and complex data sets with advanced statistical procedures that help ensure high accuracy and quality decision making.
• Use extensions, Python and R programming language code to integrate with open source software.
• More easily select and manage your software with flexible deployment options.
SPSS Statistics is available for Windows and Mac operating systems.
A powerful statistical analysis software platform
Easy to use
Perform powerful analysis and easily build visualizations and reports through a point-and-click interface, and without any coding experience.
Efficient data conditioning
Reduce data preparation time by identifying invalid values, viewing patterns of missing data, and summarizing variable distributions.
Quick and reliable
Analyze large data sets and prepare data in a single step with Automated Data Preparation.
Run advanced and descriptive statistics, regression and more with an integrated interface. Plus, you can automate common tasks through syntax.
Open source integration
Enhance SPSS syntax with R and Python using a library of extensions or by building your own.
Store files and data on your computer rather than in the cloud with SPSS that’s installed locally.
Explore advanced statistical procedures with SPSS Statistics
Use univariate and multivariate modeling for more accurate conclusions in analyzing complex relationships.
Easily summarize large data sets.
Predict categorical outcomes and apply nonlinear regression procedures.
Use classification and decision trees to help identify groups and relationships and predict outcomes.
Easily identify the right customers and improve campaign results.
Build time-series forecasts regardless of your skill level.
Discover complex relationships and improve predictive models.
Predict outcomes and reveal relationships using categorical data.
Analyze statistical data and interpret survey results from complex samples.
Better understand and measure purchasing decisions.
Reach more accurate conclusions with small samples or rare occurrences.
Uncover missing data patterns, estimate summary statistics and impute missing values.