Applied Nonparametric Statistical Methods
暫譯: 應用非參數統計方法

非參數統計方法最小化了對所分析數據分佈所需假設的數量，這與傳統的參數方法不同。因此，它們是統計學家工具箱中不可或缺的一部分，而本書則是其應用的重要資源。本書從統計學的基本概念開始，帶領讀者了解主要的非參數方法，並強調通過使用 R 程式語言進行仔細解釋的範例。

本次全面修訂和擴展的第五版的主要特點包括：

- 一個介紹性章節，提供對統計學基本概念的溫和介紹，包括數據類型、假設檢驗、信賴區間和倫理問題
- 一個 R 套件，包含為文本中的範例和練習編寫的函數
- 每個部分結尾的摘要要點，幫助讀者快速定位重要原則
- 一個來自醫學研究的案例研究，以展示非參數方法在數據分析中的應用
- 完全融入文本中的範例，來自當代問題的已發表研究，並在解釋中提供更多細節
- 大量練習題及完整解答，讓讀者測試對材料的理解
- 用於範例和練習的文章經過精心挑選，使讀者能夠識別其領域中的最新文獻，以便於研究、出版和教學材料
- 文中包含大量歷史參考，供讀者探索非參數方法的起源

《應用非參數統計方法，第五版》是一本全面的非參數技術課程教材，適合數學和統計學的本科生。它僅假設讀者具備基本的統計學經驗，並且代數內容保持在最低限度，因此也非常適合提供給本科或研究生的科學、商業和健康服務培訓中的定量方法模塊。對於研究人員、醫療從業者、商業經理、研發人員以及其他需要解釋定量信息的人士來說，這是一本寶貴的資源。適合用於持續專業發展的自學，也可作為方便的參考手冊。

Nigel Smeeton commenced his career as the Statistical Assistant at Leeds University in the Department of Statistics, teaching statistics to undergraduate and postgraduate students, and running the statistical advisory service. He then joined the General Practice Research Unit at the Institute of Psychiatry, London, focusing on the modelling of episodes of mental illness, classification of mental illness, and repetition of attempted suicide. Moving to the United Medical and Dental Schools (now part of King's College London), he specialised in stroke and asthma epidemiology. Having established the undergraduate (BDS) course in dental statistics, he wrote the introductory text Dental Statistics Made Easy, which has run to three editions. With Peter Sprent, he co-authored the third and fourth editions of Applied Nonparametric Statistical Methods. He has been Editor of the applied statistics journal The Statistician.

He joined the Centre for Research in Public Health and Community Care, University of Hertfordshire in 2013. Having worked in the areas of adolescent behaviour and epilepsy risk, he is currently part of a UK National Institute for Health and Care Research (NIHR) funded team evaluating public health interventions. His statistical expertise and interests include capture-recapture methods, proportional hazards regression, kappa statistics and the historical development of statistical methods.

Neil Spencer is Professor of Applied Statistics and Head of the Business Research Unit and Statistical Services and Consultancy Unit in Hertfordshire Business School at the University of Hertfordshire. He completed a BSc in Applied Statistics at the University of Reading before moving to the University of Southampton for an MSc in Social Statistics and then to Lancaster University for a PhD in Applied Statistics. He then became a lecturer at Staffordshire University, where he first became involved in consultancy, and moved on to the University of Hertfordshire. He is a Chartered Statistician.

He has undertaken research in a variety of subjects, from Victorian censuses to value-added school league tables, paramedics treating patients whilst wearing protective equipment, health behaviour surveys of school children, compassion in education, creation of family memories, and surveys of gig economy workers across 13 European countries. Consultancy work has included testing the randomness of National Lottery machines (for over two decades), parish plan surveys, appearing as an expert witness, methods for in-service testing of utility meters, and others, for a range of clients large and small. He is author of the books SAS Programming: The One-Day Course and Essentials of Multivariate Data Analysis.

Peter Sprent started out as Tutor, then Lecturer in Mathematics at the University of Tasmania, where he taught undergraduate students and provided statistical support within the University and to government departments and agencies. A sabbatical at the renown British agricultural institution Rothhamsted Experimental Station resulted in an appointment at East Malling Research Station, where he focused on the application of statistical methods to agricultural science. Moving to the University of Dundee, he developed the provision of teaching in statistics and headed up the statistical consultancy service within the University. His research areas included statistical regression, the analysis of small experiments, and the mathematics of size and shape. He was appointed to a personal Chair and continued working at the University of Dundee until his retirement, when he was awarded an Emeritus Professorship.

He devoted his later life to writing texts, mostly on nonparametric statistics. In addition, determined to raise the understanding of statistics in society as a whole he published the books Taking Risks: The Science of Uncertainty and Understanding Data. With his wife Janet, a botanist, he co-produced the text Nitrogen Fixing Organisms: Pure and Applied Aspects and a guide to the mountains of north-west Scotland.

奈傑爾·史密頓在利茲大學統計系開始了他的職業生涯，擔任統計助理，教授本科生和研究生統計學，並運行統計諮詢服務。隨後，他加入倫敦精神病學研究所的全科醫學研究單位，專注於精神疾病的模型建構、精神疾病的分類以及自殺未遂的重複行為。之後，他轉到聯合醫療與牙科學校（現為倫敦國王學院的一部分），專攻中風和哮喘流行病學。在建立牙科統計的本科（BDS）課程後，他撰寫了入門書籍《牙科統計簡易入門》，該書已出版三個版本。與彼得·斯普倫特共同編寫了《應用非參數統計方法》的第三和第四版。他曾擔任應用統計期刊《統計學家》的編輯。

他於2013年加入赫特福德大學公共健康與社區護理研究中心。曾在青少年行為和癲癇風險領域工作，目前是英國國家健康與護理研究所（NIHR）資助團隊的一部分，評估公共健康干預措施。他的統計專業知識和興趣包括捕獲-重捕方法、比例風險回歸、卡帕統計以及統計方法的歷史發展。

尼爾·斯賓塞是赫特福德大學商學院應用統計學教授及商業研究單位和統計服務與諮詢單位的負責人。他在雷丁大學完成了應用統計學的學士學位，然後轉到南安普敦大學獲得社會統計學的碩士學位，接著在蘭卡斯特大學獲得應用統計學的博士學位。之後，他成為斯塔福德郡大學的講師，首次參與諮詢工作，並轉到赫特福德大學。他是一名特許統計師。

他在各種主題上進行了研究，從維多利亞時代的人口普查到增值學校聯賽表、穿著防護裝備的急救人員治療病人、學校兒童的健康行為調查、教育中的同情心、家庭記憶的創造，以及對13個歐洲國家的零工經濟工作者的調查。諮詢工作包括測試國家彩票機器的隨機性（超過二十年）、教區計劃調查、作為專家證人出庭、公共事業計量器的在職測試方法等，為各種大小客戶提供服務。他是書籍《SAS程式設計：一天課程》和《多變量數據分析要素》的作者。

彼得·斯普倫特最初在塔斯馬尼亞大學擔任導師，後來成為數學講師，教授本科生並提供統計支持給大學及政府部門和機構。在著名的英國農業機構羅斯漢斯特實驗站的休假後，他被任命到東馬林研究站，專注於統計方法在農業科學中的應用。轉到鄧迪大學後，他發展了統計教學的提供，並負責大學內的統計諮詢服務。他的研究領域包括統計回歸、小型實驗的分析以及大小和形狀的數學。他被任命為個人講座教授，並在鄧迪大學工作直到退休，退休時被授予名譽教授職稱。

他將晚年生活奉獻於撰寫文本，主要是關於非參數統計。此外，為了提高社會對統計的理解，他出版了《冒險：不確定性的科學》和《理解數據》兩本書。與他的妻子珍妮特（植物學家）共同編寫了《固氮生物：純粹與應用方面》的文本以及一本關於蘇格蘭西北部山脈的指南。