Applying Analytics: A Practical Introduction

by E. S. Levine

Overview

Newcomers to quantitative analysis need practical guidance on how to analyze data in the real world yet most introductory books focus on lengthy derivations and justifications instead of practical techniques. Covering the technical and professional skills needed by analysts in the academic, private, and public sectors, Applying Analytics: A Practical Introduction systematically teaches novices how to apply algorithms to real data and how to recognize potential pitfalls. It offers one of the first textbooks for the emerging first course in analytics.

The text concentrates on the interpretation, strengths, and weaknesses of analytical techniques, along with challenges encountered by analysts in their daily work. The author shares various lessons learned from applying analytics in the real world. He supplements the technical material with coverage of professional skills traditionally learned through experience, such as project management, analytic communication, and using analysis to inform decisions. Example data sets used in the text are available for download online so that readers can test their own analytic routines.

Suitable for beginning analysts in the sciences, business, engineering, and government, this book provides an accessible, example-driven introduction to the emerging field of analytics. It shows how to interpret data and identify trends across a range of fields.

Product Details

ISBN-13:	9780367379865
Publisher:	Taylor & Francis
Publication date:	09/23/2019
Pages:	290
Product dimensions:	6.12(w) x 9.19(h) x (d)

About the Author

Dr. Evan S. Levine is an analytics professional specializing in homeland security and counterterrorism. His work has been published in Science, Risk Analysis, Analytics magazine, and several other peer-reviewed journals. He is a member of the American Association for the Advancement of Science (AAAS), the Institute For Operations Research and Management Science (INFORMS), and the Society for Risk Analysis (SRA). He earned a Ph.D. in astrophysics from the University of California, Berkeley, and a Master of Advanced Study (MASt) in mathematics from Cambridge University.

Table of Contents

Introduction. Elements. Lists. Uncertainty and Error. 1-Dimensional Data Sets. Related Lists and 1-Dimensional Data Sets. 2-Dimensional Data Sets. Unstructured Data Sets. Prescriptive Decision Analysis. Project Management. Communicating Analytic Findings. What to Do Next. Bibliography. Index.