Statistics in engineering : a practical approach

Why Understand Statistics? Probability in Engineering Decisions: Introduction. Defining Probability. The Addition Rule of Probability. Conditional Probability. Arrangements and Choices. Decision Trees. Summary. Justifying Engineering Decisions: Presenting Data. Summarising Data. Fatigue Damage. Shape of Distributions. Summary. Modelling Variability: Discrete Probability Distributions. Continuous Probability Distributions. Modelling Rainfall. Summary. Combining Variables: Introductions. Sample Covariance and Correlation. Joint Probability Distributions. Population Covariance and Correlation. Linear Combination of Random Variables. Distribution of the Sample Mean. Statistical Process Control Charts. Nonlinear Functions of Random Variables. Summary. Precision of Estimates: Precision of Means. Precision of Standard Deviations. Comparing Standard Deviations. Comparing Means. Sample Size. Proportions. Random Breath Tests? Summary. Asset Management Plan: Background. Statistical Issues. Sampling Scheme. Unit Cost Formulae. Zone Costs. Stratum Costs. Total Costs of Local Distribution Networks. Discussion. Summary. Making Predictions from One Variable: Linear Regression. Intrinsically Linear Models. Conditional Distributions. Relationship Between Correlation and Regression. Fitting Straight Lines When Both Variables Subject to Error. Calibration Lines. Summary. Making Predictions from Several Explanatory Variables: Regression on Two Explanatory Variables. Multiple Regression Model. Categorical Variables. Chrome Plating of Rods for Hydraulic Machinery. Summary. Design of Experiments: Evolutionary Operation. More Than Two Factors. Comparing Several Means. Experimental Design for Welded Joints. Summary. Modelling Variability in Time and Space: Evaluation of Mini-Roundabouts as a Road Safety Measure. Predicting Short Term Flood Risk. Spectral Analysis for Design of Offshore Structures. Endnote. Appendices: Appendix A: Mathematical Explanations of Key Results: Derivation of Poisson Distribution. Central Limit Theorem. Derivation of EVGI Distribution. Estimated Variance of Ratio Estimator. Multiple Regression Model. Du Mouchel's Algorithm. Appendix B: Reference Guide: Notation. Glossary. Problem Solving Guide. Suggested Short Course. Appendix C: Summary of Minitab Commands Used in Text. Appendix D: Data Sets. Tables. Appendix E: Statistical Tables. Appendix F: Answers to Selected Exercises.