Chapters 1 and 2 give the reader the necessary background material on probability and distribution theory. Chapter 3 discusses the most

widely used discrete and continuous probability distributions. Chapter 4 contains topics in basic inference as described above. Chapter 5 presents large sample theory on convergence in probability and distribution and ends with the Central Limit Theorem. Chapter 6 provides a complete inference (estimation and testing) based on maximum likelihood theory. Chapters 7–8 contain material on sufficient statistics and optimal tests of hypotheses.