Transportation Statistics and Microsimulation

By discussing statistical concepts in the context of transportation planning and operations, Transportation Statistics and Microsimulation provides the necessary background for making informed transportation-related decisions. It explains the why behind standard methods and uses real-world transportation examples and problems to illustrate key concepts. The Tools and Methods to Solve Transportation Problems Classroom-tested at Texas A&M University, the text covers the statistical techniques most frequently employed by transportation and pavement professionals. To familiarize readers with the underlying theory and equations, it contains problems that can be solved using statistical software. The authors encourage the use of SAS's JMP package, which enables users to interactively explore and visualize data. Students can buy their own copy of JMP at a reduced price via a postcard in the book. Practical Examples Show How the Methods Are Used in Action Drawing on the authors' extensive application of statistical techniques in transportation research and teaching, this textbook explicitly defines the underlying assumptions of the techniques and shows how they are used in practice. It presents terms from both a statistical and a transportation perspective, making conversations between transportation professionals and statisticians smoother and more productive.

Clifford Spiegelman is a distinguished professor of statistics at Texas A&M University, where he has been for twenty-three years. Dr. Spiegelman is also a senior research scientist at the Texas Transportation Institute. Eun Sug Park is a research scientist at the Texas Transportation Institute. Dr. Park was a recipient of the TRB Pedestrian Committee Outstanding Paper Award (2006 and 2009) and the Patricia Waller Award (2009). Laurence R. Rilett is a distinguished professor of civil engineering at the University of Nebraska-Lincoln. He also is the director of both the U.S. Department of Transportation's Region VII University Transportation Center and the Nebraska Transportation Center.

Overview: The Role of Statistics in Transportation Engineering. Graphical Methods for Displaying Data. Numerical Summary Measures. Probability and Random Variables. Common Probability Distributions. Sampling Distributions. Inferences: Hypothesis Testing and Interval Estimation. Other Inferential Procedures: ANOVA and Distribution-Free Tests. Inferences Concerning Categorical Data. Linear Regression. Regression Models for Count Data. Experimental Design. Cross-Validation, Jackknife, and Bootstrap Methods for Obtaining Standard Errors. Bayesian Approaches to Transportation Data Analysis. Microsimulation. Appendix.