Statistical Techniques for Transportation Engineering

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Language: English
Cover of the book Statistical Techniques for Transportation Engineering

Keywords

Addition theorem on probability; Assumptions; Assumptions for t-test; Axiomatic theory of probability; Baye' s theorem on probability; Binomial distributions and testing of hypothesis; Calculation of expected frequencies; Central limit theorem; Chi-square distribution; Classical probability; Coefficient of correlation; Coefficient of quartile deviation; Coefficient of range; Coefficient of variance; Components of time series; Computation of test statistic Z; Conditions for using chi-square; Confidence bounds; Correlation; Discrete distributions and uniform distribution; Discrete functions; Finite correction factor; Fitting a parabola and fitting exponential curve; Free-hand method; Joint distributions; Joint probability function; Least square line; Least square method; Marginal density function; Mathematical expectation; Mean of chi-square distribution; Measure of central tendency; Measure of dispersion; Measures of central tendency; Measures of dispersion; Moment generation function; Moments; Moments about mean; Moving average method; Multiplication theorem on probability; Normal distribution; Normal equations; One-way ANOVA; Population; Probability; Rank correlation coefficient; Regression; Regression equations and multilinear regression; Relative frequency approach of probability; Sample; Sample size determination; Sampling with replacement; Sampling without replacement and central limit theorem; Scatter diagram; Semiaverage method; Significance of values of t; Skewness and kurtosis; Standard error of mean; Systematic sampling; Test for goodness of fit; Test for independence of attributes and homogeneity chi-square; Test of significance for single proportion and confidence intervals; Test of significance of mean for large sample; Two-way ANOVA; Types of t-test; Uses of t-distribution; Variance of chi-square distribution

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Statistical Techniques for Transportation Engineering is written with a systematic approach in mind and covers a full range of data analysis topics, from the introductory level (basic probability, measures of dispersion, random variable, discrete and continuous distributions) through more generally used techniques (common statistical distributions, hypothesis testing), to advanced analysis and statistical modeling techniques (regression, AnoVa, and time series). The book also provides worked out examples and solved problems for a wide variety of transportation engineering challenges.

1. An Overview of Statistical Applications2. Preliminaries3. Probability4. Random Variables5. Curve Fitting6. Correlation and Regression7. Sampling8. Hypothesis Testing9. Chi-Square Distribution10. Test of Significance—Small Samples11. ANOVA (Analysis of Variance)12. Analysis of Time Series13. Index Numbers

Civil Engineers, Transportation Engineers

Professor, Head of Civil Engineering and Director of Infrastructure, Osmania University, Hyderabad, Telangana State. He published over 55 research papers in various international and National journals and conferences.
G. Shanker Rao has over 35 years of teaching experience. He has been teaching Numerical Analysis, Operations Research, Statisics and Graph Theory for the last 25 years. Presently he is a member of staff in the Department of Mathematics at University College of Engineering (A), Osmania University.
  • Demonstrates how to effectively interpret, summarize, and report transportation data using appropriate statistical descriptors
  • Teaches how to identify and apply appropriate analysis methods for transportation data
  • Explains how to evaluate transportation proposals and schemes with statistical rigor