…https://www.amazon.com/Econometric-Analysis-Cross-Section-Pa... Greene is a really useful reference text: https://www.amazon.com/Econometric-Analysis-8th-William-Gree... For advanced stats theory, I recommend Casella and Berger https://www.amazon.com/Statistical-Inference-George-Casella/... Hope that helps! The more specific a model can be made to the problem at hand, the better it'll perform. Supervised ML models are great starting / baseline models.
Depends where you are starting from and what you want to learn. The linked book is a first year introduction, and does a good job of that. If you want to go further there are many other options: * Statistical Inference by Casella and Berger. This book has a very good reputation for building statistics from first principles. I won't link to them, but you can find full PDF scans online with a simple search. Amazon reviews:…
……做机器学习的每个人都应该（彻底）搞懂下面这本中级统计学教材里的几乎全部内容：1.) Casella, G. 和 Berger, R.L. (2001). 《Statistical Inference》 Duxbury Press。如果要找一本更进阶、数学技巧推导十分透彻的书，下面这本相当不错：2.) Ferguson, T. (1996). 《A Course in Large Sample Theory》……
…that everyone in machine learning should be (completely) familiar with essentially all of the material in the following intermediate-level statistics book: 1.) Casella, G. and Berger, R.L. (2001). "Statistical Inference" Duxbury Press. For a slightly more advanced book that's quite clear on mathematical techniques, the following book is quite good: 2.) Ferguson, T. (1996). "A Course in Large Sample Theory"…
I've said this elsewhere, but I recommend Casella & Berger's Statistical Inference. It will take you from probability theory to statistics... all the basics. I found it to be a very readable text, and it is used for many first graduate courses in stats - for me it was used for a 2…
我最近一直在死磕 George Casella 的《Statistical Inference》作为打底教材，痛并快乐着。几年前亚利桑那州立大学统计学研究生入门用的就是这本。Harald Cramér 的《Mathematical Methods of Statistics》……
I've been enjoying the struggle through Statistical Inference by George Casella as a foundational text. This was the introductory text for stats graduate students at Arizona State University a few years back. The Mathematical Methods of Statistics by Harald Cramér…
…Spivak's Calculus is hands down the best intro Calc book if you want to learn math for its own sake. His book on manifolds is also amazing but definitely not intro. If you want stats I highly recommend Statistical Inference by Casella & Berger -- it's extremely dry but so many stats books out there try to "make it easy" but the simplification means that you can't actually grok what's really going on. HOWEVER if you want…
……https://www.amazon.com/Econometric-Analysis-Cross-Section-Pa... Greene 是一本非常实用的参考工具书：https://www.amazon.com/Econometric-Analysis-8th-William-Gree... 高等统计理论的话，我推荐 Casella 和 Berger 的书 https://www.amazon.com/Statistical-Inference-George-Casella/... 希望能帮到你！模型针对手头的问题定制得越具体，表现就会越好。监督 ML 模型是非常好的起点 / baseline 模型。
…https://www.amazon.com/Econometric-Analysis-Cross-Section-Pa... Greene is a really useful reference text: https://www.amazon.com/Econometric-Analysis-8th-William-Gree... For advanced stats theory, I recommend Casella and Berger https://www.amazon.com/Statistical-Inference-George-Casella/... Hope that helps! The more specific a model can be made to the problem at hand, the better it'll perform. Supervised ML models are great starting / baseline models.
这取决于你的起点以及你想学什么。链接里的书是大一入门级的，完成度很不错。如果你想更进一步，还有很多其他选择：* Casella 和 Berger 的《Statistical Inference》。这本书在从第一性原理构建统计学方面口碑极佳。我就不贴链接了，但你随便搜一下就能在网上找到完整的扫描版 PDF。Amazon 评价：……
Depends where you are starting from and what you want to learn. The linked book is a first year introduction, and does a good job of that. If you want to go further there are many other options: * Statistical Inference by Casella and Berger. This book has a very good reputation for building statistics from first principles. I won't link to them, but you can find full PDF scans online with a simple search. Amazon reviews:…
……做机器学习的每个人都应该（彻底）搞懂下面这本中级统计学教材里的几乎全部内容：1.) Casella, G. 和 Berger, R.L. (2001). 《Statistical Inference》 Duxbury Press。如果要找一本更进阶、数学技巧推导十分透彻的书，下面这本相当不错：2.) Ferguson, T. (1996). 《A Course in Large Sample Theory》……
…that everyone in machine learning should be (completely) familiar with essentially all of the material in the following intermediate-level statistics book: 1.) Casella, G. and Berger, R.L. (2001). "Statistical Inference" Duxbury Press. For a slightly more advanced book that's quite clear on mathematical techniques, the following book is quite good: 2.) Ferguson, T. (1996). "A Course in Large Sample Theory"…
我在别的地方也说过，但我还是要推荐 Casella & Berger 的《Statistical Inference》。它会带你一路从概率论打通到统计学……覆盖全部基础。我觉得它的可读性非常强，很多统计学研究生第一年的课都用它——对我来说，它是用在了一门 2……
I've said this elsewhere, but I recommend Casella & Berger's Statistical Inference. It will take you from probability theory to statistics... all the basics. I found it to be a very readable text, and it is used for many first graduate courses in stats - for me it was used for a 2…
我最近一直在死磕 George Casella 的《Statistical Inference》作为打底教材，痛并快乐着。几年前亚利桑那州立大学统计学研究生入门用的就是这本。Harald Cramér 的《Mathematical Methods of Statistics》……
I've been enjoying the struggle through Statistical Inference by George Casella as a foundational text. This was the introductory text for stats graduate students at Arizona State University a few years back. The Mathematical Methods of Statistics by Harald Cramér…
……如果你单纯为了数学本身而学数学，Spivak 的《Calculus》毫无疑问是最好的入门微积分书。他那本讲流形（manifolds）的书也很绝，但绝对不是入门向的。如果你想学统计，我强烈推荐 Casella & Berger 的《Statistical Inference》——虽然枯燥得要死，但市面上太多统计书总想“通俗易懂”，可那种简化意味着你根本无法真正 grok（参透）底层的实质。不过，如果你想……
…Spivak's Calculus is hands down the best intro Calc book if you want to learn math for its own sake. His book on manifolds is also amazing but definitely not intro. If you want stats I highly recommend Statistical Inference by Casella & Berger -- it's extremely dry but so many stats books out there try to "make it easy" but the simplification means that you can't actually grok what's really going on. HOWEVER if you want…