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This assignment builds on the definition of an "application" from Eric Siegel's (2013/2016) Predictive analytics: The power to predict who will click, buy, lie or die. Applications of data science, along with many data science methods or techniques, are discussed in Davenport & Harris (2017), and demonstrated in each chapter of Thomas Miller's (2015) Modeling Techniques in Predictive Analytics

Details of the applications paper are below, and are also discussed during a Week 2 sync session (recording will be posted in Module 2). The sync session and recording will describe the assignment, and include discussion of peer-reviewed articles, formatting, grading, and a list of data science methods found in Miller (2015).

Chapters from Siegel's book 182 Examples of Predictive Analytics that are relevant to the assignment are available in Course Reserves, and include Chapter 1: "Liftoff: Prediction Takes Action," "Appendix A: Five Effects of Prediction," and "Appendix B: Twenty-One Applications of Predictive Analytics."

Assignment

Pick an application of data science and write:

1. An introductory paragraph describing the data science application.
2. A review of the methods used in this application area.
3. Its contribution of the area to management.

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