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Your ultimate guide to SPSS Statistics vs SPSS Modeler

By NITIN MATHUR posted Thu November 14, 2019 01:59 PM

Your ultimate guide to SPSS Statistics vs SPSS Modeler

IBM’s SPSS Software is an integrated family of products that primarily consists of SPSS Statistics, SPSS Modeler and SPSS Amos. Both SPSS Statistics and Modeler enable users to build predictive models and execute other analytics tasks. Both applications were built to help business users perform complex statistical analysis to solve business and research problems quickly and efficiently.

One often comes across this question about which software to buy and what exactly is then the difference between both of them. The simple answer is that SPSS Statistics excels at making sense of complex patterns and associations- enabling you to draw conclusions and make predictions on your own or with open source integrations. And it's fast- handling tasks such as data manipulation and statistical procedures in a third of the time of many nonstatistical programs.

IBM SPSS Modeler is a visual, drag-and-drop tool that speeds operational tasks for data scientists and data analysts, accelerating time to value.  It enables users to consolidate all types of data sets from dispersed data sources across the organization and build predictive models – all without the requirement of writing code.  SPSS Modeler offers multiple machine learning techniques — including classification, segmentation and association algorithms including out-of-the-box algorithms that leverage Python and Spark. And users can now employ languages such as R and Python to extend modeling capabilities.

To make it simple, SPSS Statistics supports a more top-down, hypothesis-testing approach towards your data while SPSS Modeler allows the patterns and models hidden in the data to expose themselves, using a bottom-up, hypothesis generation approach. I thought of putting together a more in-depth view of how both these products compare to help in your buying decision. The table below compares the two products on multiple parameters that a user would look at before making any decision.



Product name

IBM SPSS Statistics

IBM SPSS Modeler

Product description

IBM SPSS Statistics is the world’s leading statistical software. It enables you to quickly dig deeper into your data, making it a much more effective tool than spreadsheets, databases, or standard multi-dimensional tools for analytics.

SPSS Statistics excels at making sense of complex patterns and associations— enabling you to draw conclusions and make predictions. And it’s fast—handling tasks such as data manipulation and statistical procedures in a third of the time of many nonstatistical programs.

IBM SPSS Modeler is a leading visual data science and machine-learning solution. It helps enterprises accelerate time to value and achieve desired outcomes by speeding up operational tasks for data scientists. It helps in data preparation and discovery, predictive analytics, model management and deployment, and machine learning to monetize data assets.

SPSS Modeler empowers users to tap into data assets and modern applications, with complete algorithms and models that are ready for immediate use. It's suited for hybrid environments to meet robust governance and security requirements.

Initial release


Clementine 1.0/ June 1994

Current version

V28.0.1 / November 2021

18.2.2 / September 2020

Operating systems

Windows, Mac OS

Windows, Linux, Unix, Mac OS X

Major usage

Hypothesis testing approach.

Hypothesis generating approach.

General usage scenarios

Have a need for descriptive and predictive analytics.

Need to develop models that generate outcomes for operational decisions.

Data is already collected for non-analytical purposes.

Need to combine data from many sources or database tables.

Need to create regular analytical reports. SPSS Statistics is ideal for creating analytically-driven reports as well as the ability to save jobs as SPSS syntax so they can be applied to updated data.

Analyzing/ querying data mostly on ad hoc basis. Modeler is more commonly used for ‘pattern detection’ type problems than traditional reporting.

Need to test data for statistical significance as it is collected from flat files or data from a single source.

Data originally collected from customer databases and flat files that were originally collected by marketing, billing or CRM applications with analysis in mind.


Integration with R and Python code. Ability to access 100+ extensions on IBM Extension Hub, enabling users to take advantage of free libraries written in R, Python and SPSS syntax.

Extensions that provide continued improvements for use with open source products, such as R and Python.


Automate common tasks via SPSS syntax. You can also use Python and R within Stats, and create customized dialog boxes that use those languages.

Includes several types of coding and automation support like Control Language for Expression Manipulation and Scripting.


Advanced algorithms, procedures, and extensions that cover both statistical and predictive analytics.

More than 30 base machine learning algorithms.

Additional features

A robust suite of data preparation features. A recently updated Custom Dialog Builder that allows users to author their own syntax-generating UIs that can be launched from any menu and shared with other users. Reporting and job scheduling capabilities.

Enhanced support for several multithreaded analytical algorithms, including Random Trees, Tree-AS, Generalized Linear Engine, Linear-AS, Linear Support Vector Machine and Two-Step-AS clustering. Modeler also supports customized nodes, which is analogous to the Custom Dialogue Builder in Stats.

Additional functionalities

A multitude of add-on modules are available to expand the functionality of the Base edition. Complex predictive models created in SPSS Modeler can be exported and applied within SPSS Statistics.

Prepared data can be exported from IBM SPSS Statistics via XML to IBM SPSS Modeler. Within Modeler statistical procedures available in IBM SPSS Statistics can be performed.

User feedback

“I love the ‘functionality’ and its user-friendliness. I spent an aggravating summer last year working with R and am still traumatized. SPSS is over and above the best program out there...”

"Ease of use without writing syntax, but also straightforward syntax when needed. Online help resources. Can do some advanced statistical procedures.”

"More transparency and confidence, as we can always view the dataset in totality, after each step of data transformation."

"The learning curve to using this product is not steep. The program is appropriate for those who do not have a lot of background in programming, yet have to perform basic statistical analysis."

"Custom tables and macros allow us to create useful reports quickly for a broad audience."

"Automated modeling for classification, clustering, linear modeling, and forecasting is very useful."

"A lot of jobs that are stuck in Excel due to the huge numbers of rows are tackled pretty quickly."

"It's very easy to use. The drag and drop feature makes it very easy when you are building and testing the streams."

Community/ Forums

IBM SPSS Statistics Community

IBM SPSS Predictive Analytics Community

Free trial

Available | Free Trial (30 days)

Available | Free Trial (30 days)

Student edition

Yes  |  SPSS Statistics GradPack

Yes  |  SPSS Modeler Premium


Option 1: Subscription Base + Add-ons

Option 2: Perpetual/ Term License editions

SPSS Statistics Base | Standard | Professional  | Premium

Click here for details.

Option 1: Subscription

Option 2: Perpetual / Term License editions

SPSS Modeler Personal | ProfessionalPremium | Gold

Click here for details

Pricing and buy

Subscription starting at $99.00* (per user per month)  |  Click here

 For Student pricing,  visit SPSS Statistics GradPack

Subscription starting at $499.00* (per user per month)  | Click here

*Price shown excludes any applicable taxes

Go ahead, make an informed decision of choosing the right software for your advanced statistical analysis requirements.