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# ðŸ“™ Intermediate Mathematical Statistics by G. P. Beaumont (auth.) â€” download pdf

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This book covers those basic topics which usually form the core of intermediate courses in statistical theory; it is largely about estimaÂ tion and hypothesis testing. It is intended for undergraduates following courses in statistics but is also suitable preparatory readÂ ing for some postgraduate courses. It is assumed that the reader has completed an introductory course which covered probability, random variables, moments and the sampling distributions. The level of mathematics required does not go beyond first year calculus. In case the reader has not acquired much facility in handling matrices, the results in least squares estimation are first obtained directly and then given an (optional) matrix formulation. If techniques for changing from one set of variables to another have not been met, then the appendix on these topics should be studied first. The same appendix contains essential discussion of the order statistics which are frequently used for illustrative purposes. Introductory courses usually include the elements of hypothesis testing and of point and interval estimation though the treatment must perforce become rather thin since at that stage it is difficult to provide adequate justifications for some procedures-plausible though they may seem. This text discusses these important topics in considerable detail, starting from scratch. The level is nowhere advanced and proofs of asymptotic results are omitted. Methods deriving from the Bayesian point of view are gradually introduced and alternate with the more usual techniques.

- Author:
**G. P. Beaumont (auth.)** - Year:
**1980** - Publisher:
**Springer Netherlands** - Language:
**English** - ISBN:
**978-0-412-15480-5,978-94-009-5794-7**

- File size:
**8 432 998** - Format:
**pdf**

Security code:

A Course in Mathematical Statistics, Second Edition, contains enough material for a year-long course in probability and statistics for advanced undergraduate or first-year graduate students, or it can be used independently for a one-semester (or even one-...

Integrating computers into mathematical statistics courses allows students to simulate experiments and visualize their results, handle larger data sets, analyze data more quickly, and compare the results of classical methods of data analysis with those us...

Integrating computers into mathematical statistics courses allows students to simulate experiments and visualize their results, handle larger data sets, analyze data more quickly, and compare the results of classical methods of data analysis with those us...

Integrating computers into mathematical statistics courses allows students to simulate experiments and visualize their results, handle larger data sets, analyze data more quickly, and compare the results of classical methods of data analysis with those us...

A wide-ranging, extensive overview of modern mathematical statistics, this work reflects the current state of the field while being succinct and easy to grasp. The mathematical presentation is coherent and rigorous throughout.The author presents classical...

This textbook introduces the mathematical concepts and methods that underlie statistics. The course is unified, in the sense that no prior knowledge of probability theory is assumed; this is developed as needed. The book is committed to a high level of ma...

This is the first text in a generation to re-examine the purpose of the mathematical statistics course. The book's approach interweaves traditional topics with data analysis and reflects the use of the computer with close ties to the practice of statisti...

This book consists of solutions to four hundred exercises, over 95% of which are in the authorâ€™s Mathematical Statistics. That textbook covers topics in statistical theory essential for graduate students preparing for work on a Ph.D. degree in statistics....

Ivchenko G.I. Problems in mathematical statistics (Mir, 1989)(ISBN 5030015388)(1s)_MVsa_...