Author : Simon P. Washington
Publisher : Chapman and Hall/CRC
ISBN 13 : 9781584880301
Total Pages : 440 pages
Book Rating : 4.8/5 (83 download)
Book Synopsis Statistical and Econometric Methods for Transportation Data Analysis by : Simon P. Washington
Download or read book Statistical and Econometric Methods for Transportation Data Analysis written by Simon P. Washington and published by Chapman and Hall/CRC. This book was released on 2003-04-29 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the field of transportation moves toward the "total quality management" paradigm, performance-based outcomes and quantitative measures have become increasingly important. Measuring performance in the field depends heavily on modeling trends and data, which in turn requires powerful, and flexible analytical tools. To date, however, transportation professionals have lacked a unified, rigorous guide to modeling the wide range of problems they encounter in the field. Statistical and Econometric Methods for Transportation Data describes the techniques most useful for modeling the many complex aspects of transportation, such as travel demand, safety, emissions, and the environment. Taking care not to overwhelm readers with statistical theory, the authors clearly and concisely present the relevant analytical methods in quantitative chapters built on transportation case studies. Mastering this material enables readers to: Formulate research hypotheses Identify appropriate statistical and econometric models Avoid common pitfalls and misapplications of statistical methods Interpret model results correctly Ideal as both a textbook and reference, this book makes three unique contributions to transportation practice and education. First, it presents a host of analytical techniques-both common and sophisticated-used to model transportation phenomena. Second, it provides a wealth of examples and case studies, and third, it specifically targets present and future transportation professionals. It builds the foundation they need not only to apply analytical models but also to understand and interpret results published elsewhere.