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. Front cover 1 Table of Contents 8 Preface 18 Acknowledgments 24 About the Authors 26 How to Contact theAuthors and Accessthe Data Sets 28 Chapter 1: Overview 30 Chapter 2: Graphical Methods for Displaying Data 40 Chapter 3: Numerical Summary Measures 58 Chapter 4: Probability and Random Variables 76 Chapter 5: Common Probability Distributions 94 Chapter 6: Sampling Distributions 120 Chapter 7: Inferences 140 Chapter 8: Other Inferential Procedures 168 Chapter 9: Inferences Concerning Categorical Data 186 Chapter 10: Linear Regression 208 Chapter 11: Regression Models for Count Data 234 Chapter 12: Experimental Design 260 Chapter 13: Cross-Validation,Jackknife, and BootstrapMethods for Obtaining Standard Errors 286 Chapter 14: Bayesian Approachesto TransportationData Analysis 296 Chapter 15: Microsimulation 316 Appendix: Soft Modelingand Nonparametric Model Building 354 Back cover 360