Chapter 1 Probability Distributions
Chapter 2 Probability Distributions of Multidimensional Random Variables
Chapter 3 Various Probability Distributions
Chapter 4 Sampling Distribution
Chapter 5 Approximation of Sampling Distributions
Chapter 6 Estimation
Chapter 7 Black
Chapter 8 Comparison of Estimates
Chapter 9 Comparison of Blacks
Chapter 10: Analysis of Variance and Regression Analysis
Chapter 11 Bayesian Inference

Appendix I: Differentiation and Integration
Appendix II: Matrix Algebra
Appendix III: R
Appendix IV: Various distribution tables

Practice problem solutions
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References

After publishing Mathematical Statistics in 2012, I revised the book several times, added supplementary content that was not fully conveyed in the book during lectures, and supplemented the practice problems through exams.
I started preparing the manuscript for a revised edition with the intention of publishing a revised edition containing these contents after retirement, but I realized that these contents were not suitable as a textbook for undergraduate courses.
After this realization, the revised edition included answers to all the practice problems, allowing readers to check their own understanding of the text, and introduced the author's writing method to help visually convey the content of distribution theory.
This method of writing was mainly used in the representative definition of sampling distribution in Chapters 3 and 4 of the revised edition, and practice problems that can utilize this method were introduced in Chapters 4, 5, and 7.
In this process, Chapter 2 provides an explanation to enhance understanding of the meaning of conditional expectation and the variance matrix, and Chapter 3 provides an intuitive explanation of the Poisson process.