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.
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.
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.
Inhaltsangabe
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
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
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