Author(s) : Glenn J. Myatt
Publisher : Wiley
Year : Dec 2006
ISBN 10 : 047007471X
ISBN 13 : 9780470074718
Language : English
Pages : 292
File type : PDF
Size : 13 MB  (book + additional files)

The purpose of this book is to describe a practical approach for making sense out of data. A step-by-step process is introduced that is designed to help you avoid some of the common pitfalls associated with complex data analysis or data mining projects. It covers some of the more common tasks relating to the analysis of data including (1) how to summarize and interpret the data, (2) how to identify nontrivial facts, patterns, and relationships in the data, and (3) how to make predictions from the data.

The book is focused on practical approaches and contains information on how the techniques operate as well as suggestions for when and how to use the different methods. Each chapter includes a further reading section that highlights additional books and online resources that provide background and other information. At the end of selected chapters are a set of exercises designed to help in understanding the respective chapter’s materials.

Making Sense of Data educates readers on the steps and issues that need to be considered in order to successfully complete a data analysis or data mining project. The author provides clear explanations that guide the reader to make timely and accurate decisions from data in almost every field of study. A step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions. With a comprehensive collection of methods from both data analysis and data mining disciplines, this book successfully describes the issues that need to be considered, the steps that need to be taken, and appropriately treats technical topics to accomplish effective decision making from data.

TABLE OF CONTENT:
Chapter 1 - Introduction
Chapter 2 - Definition
Chapter 3 - Preparation
Chapter 4 - Tables and graphs
Chapter 5 - Statistics
Chapter 6 - Grouping
Chapter 7 - Prediction
Chapter 8 - Deployment
Chapter 9 - Conclusions


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