| 000 | 02723nam a22003975i 4500 | ||
|---|---|---|---|
| 001 | 978-0-387-28276-3 | ||
| 003 | DE-He213 | ||
| 005 | 20161121230925.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 100301s2005 xxu| s |||| 0|eng d | ||
| 020 |
_a9780387282763 _9978-0-387-28276-3 |
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| 024 | 7 |
_a10.1007/0-387-28276-9 _2doi |
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| 050 | 4 | _aQA276-280 | |
| 072 | 7 |
_aPBT _2bicssc |
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| 072 | 7 |
_aMAT029000 _2bisacsh |
|
| 082 | 0 | 4 |
_a519.5 _223 |
| 100 | 1 |
_aShao, Jun. _eauthor. |
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| 245 | 1 | 0 |
_aMathematical Statistics: Exercises and Solutions _h[electronic resource] / _cby Jun Shao. |
| 264 | 1 |
_aNew York, NY : _bSpringer New York, _c2005. |
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| 300 |
_aXXVIII, 360 p. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 505 | 0 | _aProbability Theory -- Fundamentals of Statistics -- Unbiased Estimation -- Estimation in Parametric Models -- Estimation in Nonparametric Models -- Hypothesis Tests -- Confidence Sets. | |
| 520 | _aThis book consists of four hundred exercises in mathematical statistics and their solutions, over 95% of which are in the author's Mathematical Statistics, Second Edition (Springer, 2003). For students preparing for work on a Ph.D. degree in statistics and instructors of mathematical statistics courses, this useful book provides solutions to train students for their research ability in mathematical statistics and presents many additional results and examples that complement any text in mathematical statistics. To develop problem-solving skills, two solutions and/or notes of brief discussions accompany a few exercises. The exercises are grouped into seven chapters with titles matching those in the author's Mathematical Statistics. On the other hand, the book is stand-alone because exercises and solutions are comprehensible independently of their source, and notation and terminology are explained 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. Jun Shao is Professor of Statistics at the University of Wisconsin, Madison. | ||
| 650 | 0 | _aStatistics. | |
| 650 | 1 | 4 | _aStatistics. |
| 650 | 2 | 4 | _aStatistical Theory and Methods. |
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer eBooks | |
| 776 | 0 | 8 |
_iPrinted edition: _z9780387249704 |
| 856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/0-387-28276-9 |
| 912 | _aZDB-2-SMA | ||
| 950 | _aMathematics and Statistics (Springer-11649) | ||
| 999 |
_c506004 _d506004 |
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