Explore SPSS Statistics Subscription

Base Edition

Provides a wide variety of analytics capabilities including descriptive statistics, linear regression, and presentation quality graphing and reporting. You can access multiple data formats without any size constraints. Advanced data preparation capabilities enable you to eliminate labor-intensive manual checks. You can leverage bivariate statistics procedures, factor and cluster analysis as well as bootstrapping, and extend your capabilities with R/Python.

Custom Tables and Advanced Statistics Add-on

Enables you to summarize and display your analyses in production-ready tables, exportable to Microsoft or PDF. You can present survey results using nesting, stacking and multiple response categories, and manage missing values. Also provides univariate and multivariate analytical techniques and models to improve the accuracy of your analyses. Includes non-linear and general linear models and mixed model procedures as well as logistic, 2-stage least squares regression and survival analysis.

Complex Sampling and Testing Add-on

Helps you compute statistics and standard errors from small or complex sample designs. You can predict numerical and categorical outcomes from non-simple random samples, and account for up to three stages when analyzing data from a multistage design. Also enables you to access regression with optimal scaling including lasso and elastic net. Additional features include categorical principal components analysis, multidimensional scaling and unfolding, and multiple correspondence analysis.

Forecasting and Decision Trees Add-on

Enables you to develop forecasts and predict trends using time-series data. Includes ARIMA and exponential smoothing forecasting capabilities. You can automate model parameters, and test your data for intermittency and missing values. Also features decision trees, based on four tree-growing algorithms, to help you present categorical results and discover relationships between groups. As well, you can create neural network predictive models and RFM analysis to test marketing campaigns.

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