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## Mathematical Statistics: Exercises and Solutions PDF

**Short Description – **This book consists of solutions to four hundred exercises, over 95{361e85c3304e7124b5a93d02ea5bef1f7297bc06d9e373235be63e0d43f0a08b} of which are in the author’s Mathematical Statistics. That textbook covers topics in statistical theory essential for graduate students preparing for work on a Ph.D. degree in statistics. On the other hand, this is a stand-alone book, since exercises and solutions are comprehensible independently of their source. Many solutions involve standard exercises that appear in other textbooks listed in the references. To help readers not using this book with Mathematical Statistics, lists of notation, terminology, and some probability distributions are given in the front of the book. Readers are assumed to have a good knowledge in advanced calculus. A course in real analysis or measure theory is highly recommended. If this book is used with a statistics textbook that does not include probability theory, then knowledge in measure-theoretic probability theory is required. The exercises are grouped into seven chapters with titles matching those in Mathematical Statistics.

- Title –
**Mathematical Statistics: Exercises and Solutions PDF** - Author – Jun Shao
- Pages – 384
- Size – 2.395 MB
- Available Formats – PDF

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#### Customer Reviews: –

**Love this eBook –**

If you’ve also felt that you have lots of “trees” but cannot see the “forest” that is statistics, Jun Shao’s book will solve this! He keeps his basic topic list short and focused, and shows how they underlie essentially all of statistics. Also, the first chapter on probabililty theory is also very good. I never took measure theory (nor real analysis for that matter), but his expanations and presentation are clear enough that you can pick it up pretty well. However, if you are in the same boat as me, you will need to make sure you work though his examples yourself to be sure you could repoduce what he did and you know why he got that answer — without this check, you may merely feel that you understand it, but will be missing the subtle points in the theorems — remember: in advanced math, if its not forbidden in a defintion, it’s allowed.

From there, his other chapters build nicely on one another. Starting with basic problems/motivation and fundamentals and ending at the three pillars (some would probably say raison d’etre) of statistical inference, he builds a very solid conceptual house! I have come away from this book with a much deeper appreciation and understanding of statistics. It took a while (some reviewers have cited about a year to get through this…which was correct for me!) but I am now not just more conversant in statistics, but also much more creative and flexibile in how I apply statstics, and evaluate and develop new methodologies.

Thanks Dr. Shao for creating this comprehensive and clear text!Amazon Reader

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