Transportation Statistics and Microsimulation
-35 %

Transportation Statistics and Microsimulation

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ISBN-13:
9781439800232
Einband:
Buch
Erscheinungsdatum:
01.10.2010
Seiten:
355
Autor:
Clifford H. Spiegelman
Gewicht:
680 g
Format:
236x157x25 mm
Sprache:
Englisch
Beschreibung:

Overview: The Role of Statistics in Transportation Engineering What Is Engineering? What Is Transportation Engineering? Goal of the Textbook Overview of the Textbook Who Is the Audience for This Textbook? Relax-Everything Is Fine Graphical Methods for Displaying Data Introduction Histogram Box and Whisker Plot Quantile Plot Scatter Plot Parallel Plot Time Series Plot Quality Control Plots Concluding Remarks Numerical Summary Measures Introduction Measures of Central Tendency Measures of Relative Standing Measures of Variability Measures of Association Concluding Remarks Probability and Random Variables Introduction Sample Spaces and Events Interpretation of Probability Random Variable Expectations of Random Variables Covariances and Correlation of Random Variables Computing Expected Values of Functions of Random Variables Conditional Probability Bayes' Theorem Concluding Remarks Common Probability Distributions Introduction Discrete Distributions Continuous Distributions Concluding Remarks Appendix: Table of the Most Popular Distributions in Transportation Engineering Sampling Distributions Introduction Random Sampling Sampling Distribution of a Sample Mean Sampling Distribution of a Sample Variance Sampling Distribution of a Sample Proportion Concluding Remarks Inferences: Hypothesis Testing and Interval Estimation Introduction Fundamentals of Hypothesis Testing Inferences on a Single Population Mean Inferences about Two Population Means Inferences about One Population Variance Inferences about Two Population Variances Concluding Remarks Appendix: Welch (1938) Degrees of Freedom for the Unequal Variance t-Test Other Inferential Procedures: ANOVA and Distribution-Free Tests Introduction Comparisons of More than Two Population Means Multiple Comparisons One- and Multiway ANOVA Assumptions for ANOVA Distribution-Free Tests Conclusions Inferences Concerning Categorical Data Introduction Tests and Confidence Intervals for a Single Proportion Tests and Confidence Intervals for Two Proportions Chi-Square Tests Concerning More Than Two Population Proportions The Chi-Square Goodness-of-Fit Test for Checking Distributional Assumptions Conclusions Linear Regression Introduction Simple Linear Regression Transformations Understanding and Calculating R2 Verifying the Main Assumptions in Linear Regression Comparing Two Regression Lines at a Point and Comparing Two Regression Parameters The Regression Discontinuity Design (RDD) Multiple Linear Regression Variable Selection for Regression Models Additional Collinearity Issues Concluding Remarks Regression Models for Count Data Introduction Poisson Regression Model Overdispersion Assessing Goodness of Fit of Poisson Regression Models Negative Binomial Regression Model Concluding Remarks Appendix: Maximum Likelihood Estimation Experimental Design Introduction Comparison of Direct Observation and Designed Experiments Motivation for Experimentation A Three-Factor, Two Levels per Factor Experiment Factorial Experiments Fractional Factorial Experiments Screening Designs D-Optimal and I-Optimal Designs Sample Size Determination Field and Quasi-Experiments Concluding Remarks Appendix: Choice Modeling of Experiments Cross-Validation, Jackknife, and Bootstrap Methods for Obtaining Standard Errors Introduction Methods for Standard Error Estimation When a Closed-Form Formula Is Not Available Cross-Validation The Jackknife Method for Obtaining Standard Errors Bootstrapping Concluding Remarks Bayesian Approaches to Transportation Data Analysis Introduction Fundamentals of Bayesian Statistics Bayesian Inference Concluding Remarks Microsimulation Introduction Overview of Traffic Microsimulation Models Analyzing Microsimulation Output Performance Measures Concluding Remarks Appendix: Soft Modeling and Nonparametric Model Building Homework Problems and References appear at the end of each chapter.
Unlike almost all other engineering disciplines, the practice of transportation engineering is based on the behavior of individual persons. Consequently, the commonly used statistics in transportation have unique characteristics. While typical statistics books are useful, they are not typically developed with civil engineers, let alone transportation engineers, in mind. Based on the authorsa (TM) collaborative educational and research activities over the past ten years, this book focuses on statistics used in the transportation industry. Through examples, it explores the issues behind many of the most popular techniques. The text also includes computer code for solving problems.