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$260 .00

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Hearne Software is IBM's official worldwide SPSS academic software partner, with free live chat & phone support 24 hours on weekdays & extended hours on weekends.

Buy SPSS Faculty Pack that supports you in the classroom with powerful analysis techniques that include essential tools for data analysis, data mining and survey & market research. Use exclusive resources to support effective teaching and help your students become skilled in analytics. SPSS Faculty Pack also offers fast and easy licensing that enables you to start using your new software right away.
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Summary of Features

SPSS Premium Faculty Pack Icon

Statistics Faculty Pack

  • From $260.00
  •  Keep the second as your backup
    2 Activations
  • Includes all modules & Amos
  • Windows & Mac OSX
  • Rent for 12 Months

Modeler Faculty Pack Icon

Modeler Faculty Pack

  • From $270.00
  •  Keep the second as your backup
    2 Activations
  • Basic features for Mac
  •  Text & Entity Analytics, Social Network Analysis
    Premium features for Windows
  • Rent for 12 Months


Click on the Edition to see more information and pricing

Statistics Premium Faculty Pack


Statistics Premium Faculty Pack

SPSS Premium Statistics Software IconFaculty Packs can only be sold as a single-user license that provides a cost-effective way for educators to integrate statistics, data mining, survey research, and quantitative methodology into their undergraduate or graduate course curricula. The user needs to prove they are an academic educator.

The SPSS Statistics Premium Edition Faculty Pack helps academics to easily accomplish tasks at every phase of the analytical process. It includes a broad array of fully integrated Statistics capabilities and related products for specialized analytical tasks across the enterprise. The software will improve productivity significantly and help achieve superior results for specific projects and business goals. Includes SPSS Statistics Premium, Amos, Sample Power and Visualization Designer.

The IBM SPSS Statistics Premium Edition Faculty Pack includes the following 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.

  • Data preparation streamlines the data preparation stage of the analytical process.

  • Data validity and missing values increase the chance of receiving statistically significant results.

  • Categorical and numeric data can be used to predict outcomes and reveal relationships graphically.

  • Decision trees make it easier to identify groups, discover relationships between groups and predict future events.

  • Forecasting features enable you to analyze historical data and predict trends faster.

  • Structural equation modeling tools let you build structural equation models with more accuracy than standard multivariate statistics models using intuitive drag-and-drop functionality.

  • Bootstrapping makes it simple to test the stability and reliability of models so that they produce accurate, reliable results.

  • Advanced sampling assessment and testing helps make more statistically valid inferences by incorporating the sample design into survey analysis.

  • Direct marketing and product decision-making tools help marketers identify the right customers easily and improve campaign results.

  • High-end charts and graphs make it easy to create and share and interact with compelling visualizations results on a range of platforms and smart devices.

Modeler Faculty Pack


Modeler Faculty Pack

SPSS Modeler Premium Square IconIBM SPSS Modeler Faculty pack V18 is a predictive analytics platform that helps you build accurate predictive models quickly and deliver predictive intelligence to individuals, groups, systems and the enterprise. It provides a range of advanced algorithms and analysis techniques to deliver insights in near real-time. Use it to consistently make better decisions — from the desktop or within operational systems.

SPSS Modeler Features

Analytical Decision Management

  • Automate and optimize transactional decisions by combining predictive analytics, rules and scoring to deliver recommended actions in real time.

  • Decision management capabilities enable the integration of predictive analytics and business rules into an organization’s processes to optimize and automate high-volume decisions at the point of impact.

Automated Modelling

  • Use a variety of modelling approaches in a single run and then compare the results of the different modelling methods.

  • Select which models to use in deployment, without having to run them all individually and then compare performance.

  • Choose from three automated modelling methods: Auto Classifier, Auto Numeric and Auto Cluster.

Text Analytics (Only in SPSS Modeler Premium)

  • Go beyond the analysis of structured numerical data and include information from unstructured text data, such as web activity, blog content, customer feedback, emails and social media comments.

  • Capture key concepts, themes, sentiments and trends and ultimately improve the accuracy of your predictive models.

Entity Analytics (Only in SPSS Modeler Premium)

  • Identity resolution is vital in several fields, including customer relationship management, national security, fraud detection and prevention of money laundering.

  • Improves the coherence and consistency of data by resolving like entities even when the entities do not share any key values.

Social Network Analysis (Only in SPSS Modeler Premium)

  • Social network analysis examines the relationships between social entities and the implications of these relationships on an individual’s behaviour.

  • It is particularly useful for those in telecommunications and other industries concerned about attrition (or churn).

  • By identifying groups, group leaders and whether others will be affected based on influence, predictive models can be built on an individual and enhanced with their group and social behaviour data.

Geospatial Analytics

  • Geospatial analytics explore the relationship between data elements that are tied to a geographic location.

  • When combined with current and historical data, information such as latitude and longitude, postal codes and addresses can reveal deeper insights about people and events and improve predictive accuracy.

  • Geospatial analytics is frequently used in fields such as disease surveillance, law enforcement and building and facilities management.

Modelling Algorithms

The modelling algorithms included in SPSS Modeler are:

  • Anomaly Detection. Detect unusual records with a cluster-based algorithm.

  • Apriori. Identify the frequent individual items in your transactional databases and extend them to larger item sets.

  • Bayesian Networks. Estimate conditional dependencies with graphical probabilistic models that combine the principles of graph theory, probability theory, computer science and statistics.

  • C&RT, C5.0, CHAID and QUEST. Generate decision trees, including interactive trees.

  • CARMA. Mine for association rules with support for multiple consequents and continuous feedback for deterministic and accurate results.

  • Cox regression. Calculate likely time to an event.

  • Decision List. Build interactive rules.

  • Factor/PCA, Feature Selection. Reduce data.

  • Generalized Spatial Association Rule: Find patterns/association rules where location matters.

  • K-Means, Kohonen, Two Step, Discriminant, Support Vector Machine (SVM). Cluster and segment data.

  • KNN. Model and score nearest neighbour.

  • Logistic Regression. Generate binary outcomes.

  • Neural Networks. Take advantage of multilayer perceptrons with back-propagation learning and radial basis function networks.

  • Regression, Linear, GenLin (GLM), Generalized Linear Mixed Models (GLMM). Model linear equations.

  • Self-learning response model (SLRM). Take advantage of a Bayesian model with incremental learning.

  • Sequence. Conduct order-sensitive analysis with sequential association algorithm.

  • Spatial-Temporal Prediction (STP). Predict how a place will change over time.

  • Support Vector Machine. Apply non-linear functions based on computational learning theory for efficient learning on wide datasets.

  • Time-series. Generate and automatically select time-series forecasting models using techniques such as temporal causal modelling, which discovers causal relationships among large numbers of series.

  • Two-step clustering: Identify data points by similarity and group them into clusters.