The major differences between this edition and the fifth edition are :
- It is easier to find various items because more definitions,
equations, and theorems are given by chapter, section, and
display numbers. Moreover, many theorems, definitions, and
examples are given names in bold faced type for easire
reference.
- Many of the distribution finding techniques, such as
transformations and moment generating methods, are in the
first three chapters. The concepts of expectation and
conditional expectation are treated more thoroughly in the first
two chapters.
- Chapter 3 on special distributions now includes contaminated
normal distributions, the multivariate normal distribution, the t-
and F-distributions, and a section on mixture distributions.
- Chapter 4 presents large sample theory on convergence in
probablity and distribution and ends with the Central Limit
Theorem. In the first semester, if the instructor is pressed for
time he or she can omit this chapter and proceed to Chapter 5.
1. Probability and Distributions
2. Multivariate Distributions
3. Some Special Distributions
4. Unbiasedness, Consistency, and Limiting Distributions
5. Some Elementary Statistical Inferences
6. Maximum Likelihood Methods
7. Sufficiency
8. Optimal Tests of Hypotheses
9. Inferences about Normal Models
10. Nonparametric Statistics
,etc.