Decision management: Concepts, methodologies, tools, and applications
Predictive analytics and modeling are analytical tools for knowledge discovery through examining and capturing the complex relationships and patterns among the variables in the existing data in efforts to predict the future organizational performances. Their uses become more common place due largely to collecting massive amount of data, which is referred to as "big data," and the increased need to transform large amounts of data into intelligent information (knowledge) such as trends, patterns, and relationships. The intelligent information can then be used to make smart and informed data-based decisions and predictions using various methods of predictive analytics. The main purpose of this chapter is to present a conceptual and practical overview of some of the basic and advanced analytical tools of predictive analytics. The chapter provides a detailed coverage of some of the predictive analytics tools such as Simple and Multiple-Regression, Polynomial Regression, Logistic Regression, Discriminant Analysis, and Multilevel Modeling.
Link to Published Version
Kalaian, S. A., & Kasim, R. M. (2017). Predictive analytics. In Information Resources Management Association (Ed.), Decision management: Concepts, methodologies, tools, and applications. IGI Global. https://doi.org/10.4018/978-1-5225-1837-2