Clifford Spiegelman, Eun Sug Park, Laurence R. Rilett

Transportation Statistics and Microsimulation (eBook, PDF)

• Format: PDF

Produktbeschreibung

By discussing statistical concepts in the context of transportation planning and operations, this text 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 book 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 SAS's JMP package, which enables users to interactively explore and visualize data.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 384
• Erscheinungstermin: 19. April 2016
• Englisch
• ISBN-13: 9781439894545
• Artikelnr.: 56962714

Autorenporträt

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.

Inhaltsangabe

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.