Statistical and Econometric Methods for Transportation Data Analysis

Describes the techniques useful for modeling the many complex aspects of transportation, such as travel demand, safety, emissions, and the environment. This book enables readers to: formulate research hypotheses, identify appropriate statistical and econometric models, and avoid common pitfalls and misapplications of statistical methods.

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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.