Predictive Analytics

Predictive Analytics

Sema A. Kalaian, Rafa M. Kasim
ISBN13: 9781522518372|ISBN10: 1522518371|EISBN13: 9781522518389
DOI: 10.4018/978-1-5225-1837-2.ch004
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MLA

Kalaian, Sema A., and Rafa M. Kasim. "Predictive Analytics." Decision Management: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2017, pp. 49-66. https://doi.org/10.4018/978-1-5225-1837-2.ch004

APA

Kalaian, S. A. & Kasim, R. M. (2017). Predictive Analytics. In I. Management Association (Ed.), Decision Management: Concepts, Methodologies, Tools, and Applications (pp. 49-66). IGI Global. https://doi.org/10.4018/978-1-5225-1837-2.ch004

Chicago

Kalaian, Sema A., and Rafa M. Kasim. "Predictive Analytics." In Decision Management: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 49-66. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-1837-2.ch004

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Abstract

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.

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