1. Basic concepts of reliability function or hazard rate (failure rate) and expressions of these terms for popular probability distributions widely used in engineering fields.
2. Fitting life-testing data with popular distributions and checking goodness of fit.
3. Limit theorems (or, asymptotic results) and their applications in reliability theory.
4. Classical estimation of model parameters and reliability functions and simulation
5. Bayesian estimation of model parameters in a decision-theoretic set-up and simulation
6. Application of bootstrap methods in reliability studies.
7. Open discussion on real data sets.