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.
♦ Understand large and complex data sets quickly 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.
♦ Select and manage your software easily, with flexible deployment options.
SPSS Statistics is available for Microsoft Windows and the Mac operating system.
Ease of 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.
Comprehensive
Run advanced descriptive statistics, regression, and ore with an integrated interface. Plus, you can automate common tasks through syntax.
Open Source Integration
Enhance syntax with R and python using a library of extensions or by building your own.
Data Security
Store files and data on your computer rather than in the cloud with SPSS that’s installed locally.
IBM SPSS® software enables educators to teach effectively, helps students gain critical analytical skills and supports more accurate and insightful institutional research and decision-making.
For campus-wide and administrators: If you are looking to leverage the power of predictive analytics at your educational institution, SPSS Campus Edition is the product for you. Alternatively, if you are an administrator looking to improve student retention and graduation rates, SPSS has a variety of licensing options available to help you make complex decisions.
For teachers and researchers: Are you looking to teach with SPSS Software? If so, we offer the full capability of our software at a special price for education. This includes an extensive curriculum as well as a variety of teaching materials and resources. Choose SPSS Statistics Faculty Pack or SPSS Modeler MAP to help you get the most out of teaching with SPSS.
For students: Are you a student looking to expand your range of analytical skills? If so, take advantage of SPSS Statistics Gradpack, our student edition of SPSS Statistics, at a special student discount. Distinguish yourself as a future applicant in an ever-changing competitive landscape with top-notch analytical skills and a proficiency in IBM SPSS Statistics.
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
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