eBook Applying Analytics: A Practical Introduction, 1st Edition

  • E. S. Levine
  • Published By: Chapman & Hall
  • ISBN-10: 1466557192
  • ISBN-13: 9781466557192
  • DDC: 001.4
  • Grade Level Range: College Freshman - College Senior
  • 296 Pages | eBook
  • Original Copyright 2013 | Published/Released February 2016
  • This publication's content originally published in print form: 2013
  • Price:  Sign in for price



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.

Table of Contents

Front Cover.
Half Title Page.
Title Page.
Copyright Page.
1: Elements.
2: Lists.
3: Uncertainty and Error.
4: 1-Dimensional Data Sets.
5: Related Lists and 1-Dimensional Data Sets.
6: 2-Dimensional Data Sets.
7: Unstructured Data Sets.
8: Prescriptive Decision Analysis.
9: Project Management.
10: Communicating Analytic Findings.
11: What to Do Next.