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Choose from recency, frequency and monetary value (RFM) analysis, cluster analysis, prospect profiling, postal code analysis, propensity scoring and control package testing.Ĭomplex Samples Complex Samples software can compute statistics and standard errors from complex sample designs by incorporating the designs into survey analysis. You can set the conditions - control the training stopping rules and network architecture - or let the procedure choose.ĭirect Marketing Direct Marketing lets you conduct advanced analysis of your customers or contacts to help improve your results. Take advantage of multilayer perceptron (MLP) or radial basis function (RBF) procedures. Neural Networks Neural Networks uses nonlinear data modeling to discover complex relationships and derive greater value from your data. Create classification models for segmentation, stratification, prediction, data reduction and variable screening. It features visual classification and decision trees to help you present categorical results and more clearly explain analysis to non-technical audiences. Users with less expertise can create sophisticated forecasts that integrate multiple variables, while experienced forecasters can use the software to validate their models.ĭecision Trees Decision Trees enables you to identify groups, discover relationships between them and predict future events. – Preference scaling (PREFSCAL multidimensionalįorecasting Forecasting provides advanced capabilities that enable both novice and experienced users to develop reliable forecasts using time-series data. – Multidimensional scaling for individual differences
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– Nonlinear canonical correlation (OVERALS) – Ridge regression, lasso, elastic net (CATREG) – Principal components analysis for categorical data Uncover the patterns behind missing data, estimate summary statistics and impute missing values using statistical algorithms.Ĭategories – Correspondence analysis (ANACOR) Missing Values The Missing Values module helps you manage missing values in your data and draw more valid conclusions. 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 use these procedures for business and analysis projects where ordinary regression techniques are limiting or inappropriate.Ĭustom Tables Custom Tables enables you to summarize SPSS Statistics data, and display your analyses as presentation-quality, production-ready tables. Regression Regression enables you to predict categorical outcomes and apply various nonlinear regression procedures. Linear mixed-level models (aka hierarchical linear Generalized linear mixed models (GLMM) (ordinal targets included) Generalized linear models and generalized estimating equations
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It estimates sampling distribution of an estimator by resampling with replacement from the original sample.Īdvanced Statistics Advanced Statistics includes the following features: Cox regression
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– Anomaly detection-identify unusual cases in a multivariate settingīootstrapping The Bootstrapping module makes bootstrapping, a technique for testing model stability, easier. – Validate data-streamline the process of validating data before analyzing it – Automated data preparation-enhanced model viewer for automated data preparation