| 000 | 02664nam a2200409 i 4500 | ||
|---|---|---|---|
| 001 | CR9781108914062 | ||
| 003 | UkCbUP | ||
| 005 | 20240911161144.0 | ||
| 006 | m o d | ||
| 007 | cr cnu--- | ||
| 008 | 200304s2021||||enk o ||1 0|eng|d | ||
| 020 | _a9781108823418 | ||
| 040 |
_aUkCbUP _beng _erda _cUkCbUP _dNUSCL |
||
| 082 | _a519.502 EFR 2021 | ||
| 090 |
_aQA276.4 _b.E377 2021 |
||
| 100 | 1 |
_aEfron, Bradley. _eauthor. |
|
| 245 | 1 | 0 |
_aComputer age statistical inference _balgorithms, evidence, and data science / _cBradley Efron, Trevor Hastie. |
| 250 | _aStudent edition. | ||
| 264 | 1 |
_aCambridge : _bCambridge University Press, _c2021. |
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| 300 |
_a1 online resource (xix, 492 pages) : _bdigital, PDF file(s). |
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| 336 |
_atext _btxt _2rdacontent. |
||
| 337 |
_acomputer _bc _2rdamedia. |
||
| 338 |
_aonline resource _bcr _2rdacarrier. |
||
| 490 | 1 |
_aInstitute of Mathematical Statistics monographs ; _v6. |
|
| 500 | _aTitle from publisher's bibliographic system (viewed on 26 Oct 2021). | ||
| 506 | _aOnline version restricted to NUS staff and students only through NUSNET. | ||
| 520 | _aThe twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and influence. 'Data science' and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? How does it all fit together? Now in paperback and fortified with exercises, this book delivers a concentrated course in modern statistical thinking. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov Chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. Each chapter ends with class-tested exercises, and the book concludes with speculation on the future direction of statistics and data science. | ||
| 538 | _aMode of access: World Wide Web. | ||
| 538 | _aSystem requirements: Internet connectivity; World Wide Web browser. | ||
| 650 | 0 | _aMathematical statistics | |
| 650 | 0 | _aData processing. | |
| 700 | 1 |
_aHastie, Trevor, _eauthor. |
|
| 776 | 0 | 8 |
_iPrint version: _z9781108823418. |
| 830 | 0 |
_aInstitute of Mathematical Statistics monographs ; _v6. |
|
| 942 |
_2ddc _cBK _n0 |
||
| 956 | 4 | 0 | _uhttps://libproxy1.nus.edu.sg/login?url=https://doi.org/10.1017/9781108914062 |
| 999 |
_c413 _d413 |
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