| 000 | a | ||
|---|---|---|---|
| 999 |
_c33886 _d33886 |
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| 008 | 250424b xxu||||| |||| 00| 0 eng d | ||
| 020 | _a9781108724265 | ||
| 082 |
_a302.231 _bKOH |
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| 100 | _aKohavi, Ron | ||
| 245 | _aTrustworthy online controlled experiments : a practical guide to A/B testing | ||
| 260 |
_bCambridge University Press, _c2020 _aCambridge : |
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| 300 |
_axviii, 271 p. ; _bill. (some col.), _c23 cm. |
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| 365 |
_b30.99 _c₤ _d116.70 |
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| 504 | _aIncludes bibliographical references and index. | ||
| 520 | _aGetting numbers is easy; getting numbers you can trust is hard. This practical guide by experimentation leaders at Google, LinkedIn, and Microsoft will teach you how to accelerate innovation using trustworthy online controlled experiments, or A/B tests. Based on practical experiences at companies that each runs more than 20,000 controlled experiments a year, the authors share examples, pitfalls, and advice for students and industry professionals getting started with experiments, plus deeper dives into advanced topics for experienced practitioners who want to improve the way they and their organizations make data-driven decisions. | ||
| 650 | _aUser-generated content | ||
| 650 | _aMarketing | ||
| 650 | _aSocial Media | ||
| 650 | _aConfidence interval | ||
| 650 | _aDelta method | ||
| 650 | _aGuardrail metrics | ||
| 650 | _aInstitutional memory | ||
| 650 | _aNull hypothesis | ||
| 650 | _aOnline controlled experiments | ||
| 650 | _aSimpson's paradox | ||
| 650 | _aTreatment effect | ||
| 650 | _aWeb beacon | ||
| 700 | _aTang, Diane. | ||
| 700 | _aXu, Ya | ||
| 942 |
_2ddc _cBK |
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