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SPSS Statistics 25 - Standard versions & prices
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IBM SPSS Statistics Standard Edition provides the basic functionality for nearly all common business and science research problems. This tool helps you to visualize data, formulate and explore hypothesis, analyse relationships between variables or find cluster in your data in no time. Even exploring and forecasting is possible!

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IBM SPSS Statistics - Standard

Fundamental analytical capabilities for a wide variety of business and research questions

The IBM SPSS Statistics Standard Edition offers the core statistical procedures business managers and analysts need to address fundamental business and research questions. This software provides tools that allow users to quickly view data, formulate hypotheses for additional testing, and carry out procedures to clarify relationships between variables, create clusters, identify trends and make predictions.

The IBM SPSS Statistics Standard edition includes the following key capabilities:

  • Linear models offer a variety of regression and advanced statistical procedures designed to fit the inherent characteristics of data describing complex relationships.
  • Nonlinear models provide the ability to apply more sophisticated models to data.
  • Simulation capabilities help analysts automatically model many possible outcomes when inputs are uncertain, improving risk analysis and decision making.
  • Customized tables enable users to easily understand their data and quickly summarize results in different styles for different audiences.

Desktop-Systems

  Windows® Mac® OS X Linux®
Further Requirements Super VGA-Monitor (800x600) or higher Resolution
For a connection to SPSS Statistics Base Server, you will need a network adapter for TCP/IP-Network protocol
Internet Explorer
Super VGA-Monitor (800x600) or higher Resolution
Webbrowser: Mozilla Firefox
Super VGA-Monitor (800x600) or higher Resolution
Webbrowser: Mozilla Firefox
Operating System Windows XP, Vista, 7, 8, 10 (32-/64-Bit) Mac OS X 10.7 (32-/64-Bit), Mac OS X 10.8 (only 64-Bit!) Debian 6.0 x86-64, Red Hat Enterprise Linux (RHEL) 5 Desktop Editions, Red Hat Enterprise Linux (RHEL) Client 6 x86-64:
  • Linux (64 bit) kernel 2.6.28-238.e15 or higher
  • FORTRAN version libgfortran.so.3
  • C++ Version libstdc++.so.6.0.10
Min. CPU Intel or AMD-x86-Processor 1 GHz or better Intel-Processor (32-/64-Bit) Intel or AMD-x86-Processor 1 GHz or better  
Min. RAM 1 GB RAM + 1 GB RAM + 1 GB RAM +
Festplattenplatz Min. 800 MB Min. 800 MB Min. 800 MB

Server-Systems

  SPSS Statistics Server
Further Requirements For Windows-, Solaris-PC's: Network adapter with TCP/IP-Network protocol
For System z-PC's: OSA-Express3 10 Gigabit Ethernet, OSA-Express3 Gigabit Ethernet, OSA-Express3 1000BASE-T Ethernet
Operating System Windows Server 2008 or 2012 (64-Bit), Red Hat Enterprise Linux 5 (32-/64-Bit), SUSE Linux Enterprise Server 10 and 11 (32-/64-Bit)

Details can be found in the the following PDF-document:System Requirements SPSS Statistics Server 22
Min. CPU  
Min. RAM 4 GB RAM +
Disk Space ca. 1 GB for the installation. Double the amount may be needed.

Linear models

  • Statistics Standard includes generalized linear mixed models (GLMM) for use with hierarchical data.
  • This software has general linear models (GLM) and mixed models procedures.
  • It includes generalized linear models (GENLIN), including widely used statistical models such as linear regression for normally distributed responses, logistic models for binary data, and loglinear models for count data. GENLIN also offers many useful statistical models through its very general model formulation.
  • Generalized estimating equations (GEE) procedures extend generalized linear models to accommodate correlated longitudinal data and clustered data.

Nonlinear models

  • Multinomial logistic regression (MLR) predicts categorical outcomes with more than two categories.
  • Binary logistic regression classifies data into two groups.
  • Nonlinear regression (NLR) and constrained nonlinear regression (CNLR) estimate parameters of nonlinear models.
  • Probit analysis evaluates the value of stimuli using a logit or probit transformation of the proportion responding

Simulation capabilities

  • Monte Carlo simulation techniques enable you to create simulated datasets based on existing data and/or known parameters when the existing data is inadequate.
  • Non-numeric variables such as “male” and “female” can be simulated without recoding them as numeric variables.
  • Existing predictive models and data can be used as the starting points for your simulation, including models exported from Automatic Linear Modeling (ALM) and IBM SPSS Modeler.
  • Associations between categorical inputs are automatically determined and used when generating data for the inputs.
  • Results are calculated over and over, using a different set of random values to produce distributions of possible outcome values and enabling users to select the best one.
  • The advanced techniques within SPSS Statistics can be used to analyze simulation results and create charts and graphs to convey outcomes and recommended actions to decision-makers.

Customized tables

  • Means or proportions are compared for demographic groups, customer segments, time periods or other categorical variables when including inferential statistics.
  • The software creates summary statistics - from simple counts for categorical variables to measures of dispersion – and sorts categories by any summary statistic used.
  • It includes three significance tests: Chi-square test of independence, comparison of column means (t test), or comparison of column proportions (z test).
  • An interactive table builder provides drag and drop capabilities for creating pivot tables.
  • Specific categories can be excluded, displays missing value cells and can add subtotals to tables.
  • Tables can be previewed in real time and modified as they are created.
  • Tables are exportable to Microsoft® Word, Excel®, PowerPoint® or HTML for use in reports.