| 000 | 01635nam a22002417a 4500 | ||
|---|---|---|---|
| 999 |
_c93211 _d93211 |
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| 005 | 20251004111950.0 | ||
| 008 | 251004b ||||| |||| 00| 0 eng d | ||
| 020 | _a9781119891796 | ||
| 041 | _aeng | ||
| 082 | 0 | 0 | _a519.54 |
| 100 | 1 |
_aDemidenko, Eugene _eauthor |
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| 245 | 1 | 0 |
_aM-statistics : _boptimal statistical inference for a small sample / _cEugene Demidenko |
| 264 | 1 |
_aHoboken, NJ : _bJohn Wiley & Sons, Inc., _c©2023. |
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| 300 |
_ax, 222 pages : _billustrations ; _c26 cm |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_aunmediated _bn _2rdamedia |
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| 338 |
_avolume _bnc _2rdacarrier |
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| 500 | _aIncludes index | ||
| 504 | _aIncludes bibliographical references : p. 215 - 217 | ||
| 520 | _a"M-statistics: A New Statistical Perspective introduces a new approach for statistical interference, redesigning the fundamentals of statistics and improving on the classical methods we already use. The author discusses the development of new criteria for efficient estimation and delves into how two methods for statistical intereference are combined under one umbrella to create 'M statistics.' This book develops novel confidence intervals and statistical tests for statistical parameters including effect size, binomial probability, and Poisson rate, ensuring unbiased tests are developed alongside this. Suitable for professionals and students alike, this theoretical book explains how new approaches work for statistical applications and is accompanied with a GitHub repository hosting the R code for every new methodology presented."-- Provided by publisher | ||
| 650 | 0 | _aMathematical statistics | |
| 942 |
_2ddc _cBK |
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