Statistical Analysis for Civil Engineers: Mathematical Theory and Applied Experiment Design is a well-researched and topically organized reference book that guides its readers, both in academia and industry, to recognize how to describe unpredictable events in a quantitative way and to learn how these events can be incorporated into practical engineering analysis that facilitates data-driven problem solving and optimization-based decision-making.
Written by experts in the field with a proven track record as educators and practicing consultancy specialists, this book has been developed in such a manner that it advances understanding of the mathematical theory underlying analytical methodology gradually. It also supports practical application through relevant worked examples in a variety of civil engineering branches, notably structural, materials, transportation, and geotechnical engineering. Through all stages of data analysis, numerical modeling and simulation, and implementation, the volume emphasizes the need to change the current perception with respect to the use of modern statistical techniques in the scientific as well as practical spheres of civil engineering.
1. 4.1: Introduction - p. 155 2. 4.2: The T-distribution - p. 155 3. 4.3: Chi-square distribution - p. 170 4. 4.4: F-distribution - p. 177 5. 4.5: Hypothesis testing - p. 186 6. 4.6: Quick test for the two-sample location problem - p. 201 7. 4.7: Applications with MINITAB - p. 206 8. 4.8: Summary - p. 210 9. 4.9: Review questions - p. 211 10. 4.10: Answers - p. 212 11. 5 Analysis of experiments for civil engineers involving single factor - p. 215 12. 6 Correlation - p. 275 13. 7 Meta-analysis in civil engineering - p. 351 14. 8 Introduction to Monte Carlo simulation in civil engineering - p. 385 15. Index - p. 413
Statistical Analysis for Civil Engineers: Mathematical Theory and Applied Experiment Design is a well-researched and topically organized reference book that guides its readers, both in academia and industry, to recognize how to describe unpredictable events in a quantitative way and to learn how these events can be incorporated into practical engineering analysis that facilitates data-driven problem solving and optimization-based decision-making.
Written by experts in the field with a proven track record as educators and practicing consultancy specialists, this book has been developed in such a manner that it advances understanding of the mathematical theory underlying analytical methodology gradually. It also supports practical application through relevant worked examples in a variety of civil engineering branches, notably structural, materials, transportation, and geotechnical engineering. Through all stages of data analysis, numerical modeling and simulation, and implementation, the volume emphasizes the need to change the current perception with respect to the use of modern statistical techniques in the scientific as well as practical spheres of civil engineering.
1. 4.1: Introduction - p. 155 2. 4.2: The T-distribution - p. 155 3. 4.3: Chi-square distribution - p. 170 4. 4.4: F-distribution - p. 177 5. 4.5: Hypothesis testing - p. 186 6. 4.6: Quick test for the two-sample location problem - p. 201 7. 4.7: Applications with MINITAB - p. 206 8. 4.8: Summary - p. 210 9. 4.9: Review questions - p. 211 10. 4.10: Answers - p. 212 11. 5 Analysis of experiments for civil engineers involving single factor - p. 215 12. 6 Correlation - p. 275 13. 7 Meta-analysis in civil engineering - p. 351 14. 8 Introduction to Monte Carlo simulation in civil engineering - p. 385 15. Index - p. 413
