McCarthy, Richard V <br/><br/>
Applying predictive analytics:  finding value in data 

 - 2nd 
 - Cham  Springer  2022 
 - xv, 274 p. 
<br/><br/> Table of contents:<br/>Front Matter<br/>Pages i-xv<br/>Download chapter PDF <br/>Introduction to Predictive Analytics<br/>Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci<br/>Pages 1-26<br/>Know Your Data: Data Preparation<br/>Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci<br/>Pages 27-54<br/>What Do Descriptive Statistics Tell Us<br/>Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci<br/>Pages 55-85<br/>Predictive Models Using Regression<br/>Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci<br/>Pages 87-121<br/>The Second of the Big 3: Decision Trees<br/>Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci<br/>Pages 123-144<br/>The Third of the Big 3: Neural Networks<br/>Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci<br/>Pages 145-173<br/>Model Comparisons and Scoring<br/>Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci<br/>Pages 175-198<br/>Finding Associations in Data Through Cluster Analysis<br/>Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci<br/>Pages 199-232<br/>Text Analytics: Using Qualitative Data to Support Quantitative Results<br/>Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci<br/>Pages 233-254<br/><br/>[https://link.springer.com/book/10.1007/978-3-030-83070-0] 
<br/><br/> The new edition of this textbook presents a practical, updated approach to predictive analytics for classroom learning. The authors focus on using analytics to solve business problems and compares several different modeling techniques, all explained from examples using the SAS Enterprise Miner software. The authors demystify complex algorithms to show how they can be utilized and explained within the context of enhancing business opportunities. Each chapter includes an opening vignette that provides real-life examples of how business analytics have been used in various aspects of organizations to solve issues or improve their results. A running case provides an example of a how to build and analyze a complex analytics model and utilize it to predict future outcomes. The new edition includes chapters on clusters and associations and text mining to support predictive models. An additional case is also included that can be used with each chapter or as a semester project.<br/><br/>(https://link.springer.com/book/10.1007/978-3-030-83070-0) 
<br/><br/><label>ISBN: </label>9783030830724 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Marketing analytics<br/>Predictive analytics
<br/><br/><label>Dewey Class. No.: </label>658.83  / MCC