關於本電子書
Relevant, concrete, and thorough--the essential data-based text onstatistical inference
The ability to formulate abstract concepts and draw conclusionsfrom data is fundamental to mastering statistics. Aspects ofStatistical Inference equips advanced undergraduate and graduatestudents with a comprehensive grounding in statistical inference,including nonstandard topics such as robustness, randomization, andfinite population inference.
A. H. Welsh goes beyond the standard texts and expertly synthesizesbroad, critical theory with concrete data and relevant topics. Thetext follows a historical framework, uses real-data sets andstatistical graphics, and treats multiparameter problems, yet isultimately about the concepts themselves.
Written with clarity and depth, Aspects of Statistical Inference:
* Provides a theoretical and historical grounding in statisticalinference that considers Bayesian, fiducial, likelihood, andfrequentist approaches
* Illustrates methods with real-data sets on diabetic retinopathy,the pharmacological effects of caffeine, stellar velocity, andindustrial experiments
* Considers multiparameter problems
* Develops large sample approximations and shows how to use them
* Presents the philosophy and application of robustness theory
* Highlights the central role of randomization in statistics
* Uses simple proofs to illuminate foundational concepts
* Contains an appendix of useful facts concerning expansions,matrices, integrals, and distribution theory
Here is the ultimate data-based text for comparing and presentingthe latest approaches to statistical inference.
The ability to formulate abstract concepts and draw conclusionsfrom data is fundamental to mastering statistics. Aspects ofStatistical Inference equips advanced undergraduate and graduatestudents with a comprehensive grounding in statistical inference,including nonstandard topics such as robustness, randomization, andfinite population inference.
A. H. Welsh goes beyond the standard texts and expertly synthesizesbroad, critical theory with concrete data and relevant topics. Thetext follows a historical framework, uses real-data sets andstatistical graphics, and treats multiparameter problems, yet isultimately about the concepts themselves.
Written with clarity and depth, Aspects of Statistical Inference:
* Provides a theoretical and historical grounding in statisticalinference that considers Bayesian, fiducial, likelihood, andfrequentist approaches
* Illustrates methods with real-data sets on diabetic retinopathy,the pharmacological effects of caffeine, stellar velocity, andindustrial experiments
* Considers multiparameter problems
* Develops large sample approximations and shows how to use them
* Presents the philosophy and application of robustness theory
* Highlights the central role of randomization in statistics
* Uses simple proofs to illuminate foundational concepts
* Contains an appendix of useful facts concerning expansions,matrices, integrals, and distribution theory
Here is the ultimate data-based text for comparing and presentingthe latest approaches to statistical inference.
關於作者
A. H. WELSH is a Reader of Statistics at the Australian National University in Canberra, Australia.
為這本電子書評分
歡迎提供意見。
閱讀資訊
智慧型手機與平板電腦
筆記型電腦和電腦
你可以使用電腦的網路瀏覽器聆聽你在 Google Play 購買的有聲書。
電子書閱讀器與其他裝置
如要在 Kobo 電子閱讀器這類電子書裝置上閱覽書籍，必須將檔案下載並傳輸到該裝置上。請按照說明中心的詳細操作說明，將檔案傳輸到支援的電子閱讀器上。
