This synthesis reviews the state of the practice in how data are analyzed. It addresses methods used to analyze data and what computer systems are used to store and process data. It also covers accuracy issues, including measurement error, and other problems including error in estimates. This document from the Transportation Research Board addresses agency experience with different data collection systems, giving attention to management error, the need for sampling, and methods for screening, editing, and compensating for data imperfection. Sample reports from selected U.S. and Canadian transit agencies are reproduced in this synthesis.

This book introduces the latest thinking on the use of Big Data in the context of urban systems, including research and insights on human behavior, urban dynamics, resource use, sustainability and spatial disparities, where it promises improved planning, management and governance in the urban sectors (e.g., transportation, energy, smart cities, crime, housing, urban and regional economies, public health, public engagement, urban governance and political systems), as well as Big Data’s utility in decision-making, and development of indicators to monitor economic and social activity, and for urban sustainability, transparency, livability, social inclusion, place-making, accessibility and resilience.

This book introduces the fundamentals of research methods and how they apply to the discipline of urban and regional planning. Written at a level appropriate for upper-level undergraduate and beginning master’s level students, the text fills a gap in the literature for textbooks on urban planning. Additionally, the book can be used as a reference for planning practitioners and researchers when analyzing quantitative and qualitative data in urban and regional planning and related fields. The volume does not assume advanced knowledge of mathematical formulas. Rather, it begins with the essentials of research methods, such as the identification of the research problems in planning, the literature review, data collection and presentation, descriptive data analysis, and report of findings. Its discipline-specific topics include field research methods, qualitative data analysis, economic and demographic analysis, evaluation research, and methods in sub-disciplines such as land use planning, transportation planning, environmental planning, and housing analysis. Designed with instruction in mind, this book features downloadable materials, including learning outcomes, chapter highlights, chapter review questions, datasets, and certain Excel models. Students will be able to download review questions to enhance the learning process and datasets to practice methods.

The 17 chapters in this book, which evolved from a conference on measuring the contributions of ITS sponsored by the California Department of Transportation in February 2002, examine the costs and benefits of ITS in an economic and business policy context. Section 1 examines the broad theme of how and what ITS contributes to the economy and how one makes a business case for ITS. Section 2 includes three chapters on ITS applications in mass transit. Section 3 explores ITS applications in the automobile/highway system. Section 4 considers integrative issues including how ITS is perceived and how it can be positioned to improve surface transportation. This volume will be especially useful to researchers and policy makers working in transportation, transportation engineering, and the economic analysis of transportation systems.

Data analytics underpin our modern data-driven economy. This textbook explains the relevance of data analytics at the firm and industry levels, tracing the evolution and key components of the field, and showing how data analytics insights can be leveraged for business results. The first section of the text covers key topics such as data analytics tools, data mining, business intelligence, customer relationship management, and cybersecurity. The chapters then take an industry focus, exploring how data analytics can be used in particular settings to strengthen business decision-making. A range of sectors are examined, including financial services, accounting, marketing, sport, health care, retail, transport, and education. With industry case studies, clear definitions of terminology, and no background knowledge required, this text supports students in gaining a solid understanding of data analytics and its practical applications. PowerPoint slides, a test bank of questions, and an instructor’s manual are also provided as online supplements. This will be a valuable text for undergraduate level courses in data analytics, data mining, business intelligence, and related areas.