Ibm Spss Help
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• • • • IBM SPSS predictive analytics software offers advanced techniques in an easy-to-use package to help you dive deep into data to find the results that matter. IBM SPSS is a very popular application on many academic courses allowing you to work more efficiently and make data-driven decisions to generate predictive insights. How to download IBM SPSS Download IBM SPSS from. • Log in where prompted with your normal University ID number and password • Click the software link to see a listing of both free and discounted software • Choose what you'd like to download and follow the instructions Learn how to use IBM SPSS Lynda.com offers video courses helping you get to grips with SPSS, such as: • As a Manchester Met student, you enjoy complimentary access to Lynda.com I've lost my license code for IBM SPSS If you downloaded SPSS from OnTheHub, you can log back in to that website and retrieve your code from there. Installed SPSS from another source? Please refer to that provider or any confirmation email received when you acquired the software. For licence numbers, please contact the on 0161 247 4646.
Ibm Spss Help
Ibm Spss Download
Predictive analytics helps connect data to effective action by drawing reliable conclusions about current conditions and future events. Predictive analytics, like enterprise resource planning (ERP) and customer relationship management (CRM), is both a business process and a set of related technologies. Predictive analytics leverages an organization’s business knowledge by applying sophisticated analysis techniques to enterprise data. The resulting insights can lead to actions that demonstrably change how people behave as customers, employees, patients, students, and citizens. The predictive analytics process begins by exploring how specific business issues relate to data describing people’s characteristics, attitudes, and behavior.
These numeric and free-form data sets, which originate from both internal systems and third party providers, are cleansed, transformed, and evaluated using statistical, mathematical, and other algorithmic techniques. These techniques generate models for classification, segmentation, forecasting, pattern recognition, sequence and association detection, anomaly identification, profiling, propensity scoring, rule induction, text mining, and advanced visualization. Combining predictive analytics models with organizational business knowledge provides insight into such critical issues as customer acquisition and retention, up-selling and cross-selling, fraud detection, and outcome improvement. Through measuring uncertainty surrounding these issues, predictive analytics enables proactive risk management, refining key decision making processes through controlled, iterative testing of potential actions and their likely intended-and unintended-consequences. These findings and their corresponding business rules can then be deployed within front-line operational systems to identify new revenue opportunities, measurable cost savings, repeatable process improvements, and sustainable competitive advantages. Predictive analytics carries strategic and tactical ramifications for organizations that recognize the inherent value locked within their existing enterprise data. Strategically, predictive analytics provides a quantitative foundation for rapidly identifying, objectively evaluating, and confidently pursuing new market opportunities.