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.