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Base package.
The Base package includes the following features:

Data access and management
– Compare two data files for compatibility
– Data prep features: Define Variable Properties tool;
Copy Data Properties tool, Visual Bander, Identify
Duplicate Cases; Date/Time wizard
– Data Restructure wizard
– Single record to multiple records
– Multiple records to single record
– Direct Excel data access
– Easier importing from Excel and CSV
– Export data to SAS and current versions of Excel
– Export/insert to Database wizard
– Import data from IBM Cognos® Business Intelligence
– Import/export to/from Dimensions
– Import Stata files (until V14)
– Long variable names
– Longer value labels
– Multiple datasets can be run in one SPSS session
– ODBC Capture—DataDirect drivers
– OLE DB data access
– Password protection
– SAS 7/8/9 data files including compressed files)
– Text wizard
– Unicode support
– Very long text strings
Data preparation
– Automated data preparation—enhanced model
viewer for automated data preparation
– Validate data—streamline the process of validating
data before analyzing it
– Anomaly detection—identify unusual cases in a
multivariate setting
– Optimal binning
Graphs
– Auto and cross correlation graphs
– Basic graphs
– Mapping (geospatial analysis)
– Chart gallery
– Chart options
– ChartBuilder UI for commonly used charts
– Charts for multiple response variables
– Graphics Production Language for custom charts
– Interactive graphs—scriptable
– Overlay and dual Y charts
– Panelled charts
– ROC analysis
– Time series charts
– Relationship map

Output
– Case summaries
– Style output
– Conditional formatting
– Codebook
– Export charts as Microsoft Graphic Object
– Export model as XML to SmartScore
– Export to PDF
– Export to Word/Excel/PowerPoint
– HTML output
Help features
– Application examples
– Index
– Tutorial
– Extensions
– Search
Data editor enhancements
– Custom attributes for user-defined metadata
– Spell checker
– Splitter controls
– Variable sets for wide data
– Variable icons
– Optimal binning
– Improved performance for large pivot tables
– OLAP cubes/pivot tables
– Output management system
– Output scripting
– Reports summaries in rows and columns
– Search and replace
– Smart devices (tablets and phones)
– Table to graph conversion
– Web reports
Extended programmability
– Custom UI builder enhancements (work seamlessly
with Python and R and can be used in IBM SPSS
Modeler)
– New Extensions hub
– Custom dialog builder for Extensions
– Flow control or syntax jobs
– Partial least squares regression
– Python, .NET and Java for front-end scripting
– SPSS equivalent of the SAS DATA STEP
– Support for R algorithms and graphics
– User-defined procedures

Statistics
– ANOVA (in syntax only)
– Automatic linear models
– Cluster
– Correlate—bivariate, partial, distances
– Crosstabs
– Define variable sets
– Descriptive ratio statistics (PVA)
– Descriptives
– Discriminant analysis
– Enhanced model viewer on two-step cluster and new
nonparametrics
– Explore
– Factor analysis
– Frequencies
– Geo-spatial analytics (STP and GSAR) (NEW!)
– Improved performance for frequencies, crosstabs,
descriptives
– Power Analysis
– (Statistics Base Server)
– Matrix operations
– Means
– Monte Carlo simulation
– Nearest neighbor analysis
– New nonparametric tests
– One way ANOVA
– Ordinal regression (PLUM)
– Ordinary least squares regression
– Power Analysis
– PP plots
– QQ plots
– Ratio
– Reliability and ALSCAL multidimensional scaling
– ROC curve
– Compare ROC curves
– Rule checking on secondary SPC charts
– Summarize data
– T tests: paired samples, independent samples, onesamples
– Two-step cluster: categorical and continuous data/
large data sets
– Weighted Cohen’s kappa
– Meta-analysis

Multithreaded algorithms
– SORT
Bootstrapping
– Sampling and pooling
– Descriptive procedures that can be bootstrapped
– Correlations/nonparametric correlations
– Crosstabs
– Descriptives
– Examine
– Frequencies
– Means
– Partial correlations
– T tests

Standard package
The Standard package includes the Base package plus the following features:

Regression
– Binary logistic regression
– Logit response models
– Multinomial logistic regression
– Nonlinear regression
– Probit response analysis
– Two stage least squares
– Weighted least squares
– Quantile regression
Advanced statistics
– Cox regression
– General linear modeling (GLM)
– General factorial
– Multivariate (MANOVA)
– Repeated measures
– Variance components
– Generalized linear models and generalized
estimating equations
– Gamma regression
– Poisson regression
– Negative binomial
– GENLOG for loglinear and logit
– Generalized linear mixed models (GLMM) (ordinal
targets included)
– Bayesian statistics
– Hierarchical loglinear models
– Kaplan Meier
– Linear mixed-level models (aka hierarchical linear
models)
– Survival
– Variance component estimation
Custom tables
– 35 descriptive statistics
– Drag and drop interface
– Inferential statistics
– Nested tables
– Place totals in any row, column, or layer
– Post computed categories
– Effective base for weighted sample results
– Put multiple variables into the same table
– Significance tests on multiple response variables
– Significance test in custom tables main table
– Significance values for column means and column
proportion tests
– Specialized multiple response set tables
– False discovery correction method for multiple
comparisons
– Syntax converter
 

Professional package
The Professional package includes Base and Standard package features, plus the following:

Forecasting
– Auto regressive integrated moving average
– Autoregression
– Expert modeler exponential smoothing methods
– Forecast multiple series (outcomes) at once
– Temporal causal modeling
– Seasonal decomposition
– Spectral analysis
Categories
– Correspondence analysis (ANACOR)
– Principal components analysis for categorical data
(CATPCA; replaces PRINCALS)
– Ridge regression, lasso, elastic net (CATREG)
– CORRESPONDENCE
– Nonlinear canonical correlation (OVERALS)
– Multidimensional scaling for individual differences
scaling with constraints (PROXSCAL)
– Preference scaling (PREFSCAL; multidimensional
unfolding)
– Multiple correspondence analysis
Missing values
– Data patterns table
– Imputation with means estimation or regression
– Listwise and pairwise statistics
– Missing patterns table
– Multiple imputation of missing data
– Pooling
Decision trees
– C&RT
– CHAID
– Exhaustive CHAID
– QUEST
Data preparation
– Automated data preparation—enhanced model viewer
for automated data preparation
– Validate data—streamline the process of validating data
before analyzing it
– Anomaly detection—identify unusual cases in a
multivariate setting
– Optimal binning

Premium package
The Premium package includes Base, Standard and Professional features plus the following:

Exact tests
– Cochran’s Q test
– Contingency coefficient
– Cramer’s V
– Fisher’s exact test
– Somers’ D—symmetric and asymmetric
– Friedman test
– Gamma
– Goodman and Kruskal tau
– Jonckheere-Terpstra test
– Kappa
– Kendall’s coefficient of concordance
– Kendall’s tau-b and tau-c
– Kruskal-Wallis test
– Likelihood ratio test
– Linear-by-linear association test
– Mann-Whitney U or Wilcoxon rank-sum W test
– Marginal homogeneity test
– McNemar test
– Median test
– Pearson Chi-square test
– Pearson’s R
– Phi
– Sign test
– Spearman correlation
– Uncertainty coefficient—symmetric or asymmetric
– Wald-Wolfowitz runs test
– Wilcoxon signed-rank test
Complex samples (CS)
– CS Cox regression (also multithreaded)
– CS descriptives
– CS general linear models
– CS logistic regression
– CS ordinal regression
– CS selection
– CS tabulate
– Sampling wizard/Analysis Plan wizard
Neural networks
– Multilayer perception
– Radial basis function
Conjoint
– Estimate utilities (CONJOINT)
– For conjoint analysis (ORTHOPLAN)
– PLANCARDS
Direct marketing
– Cluster analysis
– Contact profiling
– Control package test
– Propensity to purchase
– RFM analysis: recency, frequency, monetary
– Zip code response
AMOS (Structural Equation Modeling)
– Bayesian estimation
– Confirmatory factor analysis
– Enter the model into a spreadsheet-like table (no
programming)
– Estimation of categorical and censored data
– Latent class analysis
– Non-graphical method of modeling
– Structural equation modeling/path analysis
– Specify path diagram using syntax