Contents. PART I: INTRODUCTION 1. What is sensitivity analysis. 2. Hitchhiker's guide to sensitivity analysis. PART II: METHODS. 3. Designs of experiments. 4. Screening methods. 5. Local methods. 6. Sampling-based methods. 7. Reliability algorithms: FORM and SORM methods. 8. Variance-based methods. 9. Managing the tyranny of parameters in mathematical modelling of physical systems. 10. Bayesian sensitivity analysis. 11. Graphical methods. PART III: APPLICATIONS. 12. Practical experience in applying sensitivity and uncertainty analysis. 13. Scenario and parametric sensitivity and uncertainty analysis in nuclear waste disposal risk assessment: the case of GESAMAC. 14. Sensitivity analysis for signal extraction in economic time series. 15. A dataless precalibration analysis in solid state physics. 16. Application of first-order (FORM) and second-order (SORM) reliability methods: analysis and interpretation of sensitivity measures related to groundwater pressure decreases and resulting ground subsidence. 17. One-at-a-time and mini-global analyses for characterizing model sensitivity in the nonlinear ozone predictions from the US EPA regional acide deposition model (RADM). 18. Comparing different sensitivity analysis methods on a chemical reactions model. 19. An application of sensitivity analysis to fish population dynamics. 20. Global sensitivity analysis: a quality assurance tool in environmental policy modelling. PART IV: CONCLUSIONS. 21. Assuring the quality of model designed for predictive tasks. 22. Fortune and foture of sensitivity analysis. APPENDIX: Software for sensitivity analysis - A brief review.