Mathematical Statistics with Resampling and R, 3/e (Hardcover)

DESCRIPTION

Mathematical Statistics with Resampling and R This thoroughly updated third edition combines the latest software applications with the benefits of modern resampling techniques Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis tests, and confidence intervals. The third edition of Mathematical Statistics with Resampling and R combines modern resampling techniques and mathematical statistics. This book is classroom-tested to ensure an accessible presentation, and uses the powerful and flexible computer language R for data analysis. This book introduces permutation tests and bootstrap methods to motivate classical inference methods, as well as to be utilized as useful tools in their own right when classical methods are inaccurate or unavailable. The book strikes a balance between simulation, computing, theory, data, and applications. Throughout the book, new and updated case studies representing a diverse range of subjects, such as flight delays, birth weights of babies, U.S. demographics, views on sociological issues, and problems at Google and Instacart, illustrate the relevance of mathematical statistics to real-world applications. Changes and additions to the third edition include: New and updated case studies that incorporate contemporary subjects like COVID-19 Several new sections, including introductory material on causal models and regression methods for causal modeling in practice Modern terminology distinguishing statistical discernibility and practical importance New exercises and examples, data sets, and R code, using dplyr and ggplot2 A complete instructor’s solutions manual A new github site that contains code, data sets, additional topics, and instructor resources Mathematical Statistics with Resampling and R is an ideal textbook for undergraduate and graduate students in mathematical statistics courses, as well as practitioners and researchers looking to expand their toolkit of resampling and classical techniques.

《具有重抽樣和 R 的數學統計學》（第三版）結合了最新的軟體應用和現代重抽樣技術的優勢。重抽樣有助於學生理解抽樣分佈、抽樣變異性、P 值、假設檢驗和信賴區間的意義。《具有重抽樣和 R 的數學統計學》（第三版）結合了現代重抽樣技術和數學統計學。本書經過課堂測試，以確保易於理解的呈現方式，並使用功能強大且靈活的電腦語言 R 進行數據分析。本書介紹了排列檢驗和自助法，以激發對經典推論方法的興趣，同時在經典方法不準確或不可用時，它們也可以作為有用的工具。本書在模擬、計算、理論、數據和應用之間取得了平衡。全書通過新的和更新的案例研究展示了數學統計學對現實世界應用的相關性，這些案例研究涵蓋了各種主題，如航班延誤、嬰兒出生體重、美國人口統計、對社會學問題的觀點以及 Google 和 Instacart 的問題。第三版的變化和新增內容包括：包含當代主題（如 COVID-19）的新的和更新的案例研究；包括因果模型的入門材料和實踐中的回歸方法的新節；區分統計可辨識性和實際重要性的現代術語；新的練習和例子、數據集和使用 dplyr 和 ggplot2 的 R 代碼；完整的教師解答手冊；包含代碼、數據集、額外主題和教師資源的新的 github 網站。《具有重抽樣和 R 的數學統計學》是大學和研究生數學統計學課程的理想教材，也是希望擴展重抽樣和經典技術工具箱的從業人員和研究人員的參考書。