HOME > 상세정보

상세정보

Information quality : the potential of data and analytics to generate knowledge

Information quality : the potential of data and analytics to generate knowledge (1회 대출)

자료유형
단행본
개인저자
Kenett, Ron. Shmueli, Galit, 1971-.
서명 / 저자사항
Information quality : the potential of data and analytics to generate knowledge / Ron S. Kenett, KPA, Israel and University of Turin, Italy, Galit Shmueli, National Tsing Hua university, Taiwan.
발행사항
Chichester, West Sussex :   Wiley,   c2017.  
형태사항
xvii, 363 p. : ill. ; 24 cm.
ISBN
9781118874448 (cloth)
서지주기
Includes bibliographical references and index.
일반주제명
Data mining. Mathematical statistics.
000 00000cam u2200205 a 4500
001 000045969087
005 20190128165952
008 190128s2017 enka b 001 0 eng d
010 ▼a 2016022699
020 ▼a 9781118874448 (cloth)
020 ▼z 9781118890653 (epub)
035 ▼a (KERIS)REF000018086283
040 ▼a DLC ▼b eng ▼c DLC ▼e rda ▼d DLC ▼d 211009
050 0 0 ▼a QA276 ▼b .K4427 2017
082 0 0 ▼a 006.3/12 ▼2 23
084 ▼a 006.312 ▼2 DDCK
090 ▼a 006.312 ▼b K33i
100 1 ▼a Kenett, Ron.
245 1 0 ▼a Information quality : ▼b the potential of data and analytics to generate knowledge / ▼c Ron S. Kenett, KPA, Israel and University of Turin, Italy, Galit Shmueli, National Tsing Hua university, Taiwan.
260 ▼a Chichester, West Sussex : ▼b Wiley, ▼c c2017.
300 ▼a xvii, 363 p. : ▼b ill. ; ▼c 24 cm.
504 ▼a Includes bibliographical references and index.
650 0 ▼a Data mining.
650 0 ▼a Mathematical statistics.
700 1 ▼a Shmueli, Galit, ▼d 1971-.
945 ▼a KLPA

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 중앙도서관/서고6층/ 청구기호 006.312 K33i 등록번호 111803700 도서상태 대출가능 반납예정일 예약 서비스 B M

컨텐츠정보

저자소개

갈리트 시뮤엘리(지은이)

현재 대만 국립 칭화대학교 서비스 사이언스 연구소의 칭화 특훈교수이며, 베스트셀러인 비즈니스를 위한 데이터마이닝 책의 공동저자이다. 그동안 관련 분야에서 다수의 전문서적을 출간하였으며, 최고 학술지에 다수의 논문을 게재하였다. 또한, 시뮤엘리 교수는 인도 경영대학, 미국 메릴랜드대학교 스미스 경영대학원, 인도 경영대학 대만 국립칭화대학교, Statistics.com 등에서 예측, 데이터마이닝, 통계학, 기타 데이터 분석 등의 과목을 설계하고, 강의한 경력이 있다.

Ron Kenett(지은이)

정보제공 : Aladin

목차

Intro -- Title Page -- Copyright Page -- Contents -- Foreword -- About the authors -- Preface -- Quotes about the book -- About the companion website -- Part I The Information Quality Framework -- Chapter 1 Introduction to information quality -- 1.1 Introduction -- 1.2 Components of InfoQ -- 1.3 Definition of information quality -- 1.4 Examples from online auction studies -- 1.5 InfoQ and study quality -- 1.6 Summary -- References -- Chapter 2 Quality of goal, data quality, and analysis quality -- 2.1 Introduction -- 2.2 Data quality -- 2.3 Analysis quality -- 2.4 Quality of utility -- 2.5 Summary -- References -- Chapter 3 Dimensions of information quality and InfoQ assessment -- 3.1 Introduction -- 3.2 The eight dimensions of InfoQ -- 3.3 Assessing InfoQ -- 3.4 Example: InfoQ assessment of online auction experimental data -- 3.5 Summary -- References -- Chapter 4 InfoQ at the study design stage -- 4.1 Introduction -- 4.2 Primary versus secondary data and experiments versus observational data -- 4.3 Statistical design of experiments -- 4.4 Clinical trials and experiments with human subjects -- 4.5 Design of observational studies: Survey sampling -- 4.6 Computer experiments (simulations) -- 4.7 Multiobjective studies -- 4.8 Summary -- References -- Chapter 5 InfoQ at the postdata collection stage -- 5.1 Introduction -- 5.2 Postdata collection data -- 5.3 Data cleaning and preprocessing -- 5.4 Reweighting and bias adjustment -- 5.5 Meta-analysis -- 5.6 Retrospective experimental design analysis -- 5.7 Models that account for data “loss”: Censoring and truncation -- 5.8 Summary -- References -- Part II Applications of InfoQ -- Chapter 6 Education -- 6.1 Introduction -- 6.2 Test scores in schools -- 6.3 Value-added models for educational assessment -- 6.4 Assessing understanding of concepts -- 6.5 Summary -- Appendix: MERLO implementation for an introduction to statistics course -- References -- Chapter 7 Customer surveys -- 7.1 Introduction -- 7.2 Design of customer surveys -- 7.3 InfoQ components -- 7.4 Models for customer survey data analysis -- 7.5 InfoQ evaluation -- 7.6 Summary -- Appendix: A posteriori InfoQ improvement for survey nonresponse selection bias -- References -- Chapter 8 Healthcare -- 8.1 Introduction -- 8.2 Institute of medicine reports -- 8.3 Sant’Anna di Pisa report on the Tuscany healthcare system -- 8.4 The haemodialysis case study -- 8.5 The Geriatric Medical Center case study -- 8.6 Report of cancer incidence cluster -- 8.7 Summary -- References -- Chapter 9 Risk management -- 9.1 Introduction -- 9.2 Financial engineering, risk management, and Taleb’s quadrant -- 9.3 Risk management of OSS -- 9.4 Risk management of a telecommunication system supplier -- 9.5 Risk management in enterprise system implementation -- 9.6 Summary -- References -- Chapter 10 Official statistics -- 10.1 Introduction -- 10.2 Information quality and official statistics -- 10.3 Quality standards for official statistics -- 10.4 Standards for customer surveys -- 10.5 Integrating official statistics with administrative data for enhanced InfoQ -- 10.6 Summary -- References -- Part III Implementing InfoQ -- Chapter 11 InfoQ and reproducible research -- 11.1 Introduction -- 11.2 Definitions of reproducibility, repeatability, and replicability -- 11.3 Reproducibility and repeatability in GR&&R -- 11.4 Reproducibility and repeatability in animal behavior studies -- 11.5 Replicability in genome‐wide association studies -- 11.6 Reproducibility, repeatability, and replicability: the InfoQ lens -- 11.7 Summary -- Appendix: Gauge repeatability and reproducibility study design and analysis -- References -- Chapter 12 InfoQ in review processes of scientific publications -- 12.1 Introduction -- 12.2 Current guidelines in applied journals -- 12.3 InfoQ guidelines for reviewers -- 12.4 Summary -- References -- Chapter 13 Integrating InfoQ into data science analytics programs, research methods courses, and more -- 13.1 Introduction -- 13.2 Experience from InfoQ integrations in existing courses -- 13.3 InfoQ as an integrating theme in analytics programs -- 13.4 Designing a new analytics course (or redesigning an existing course) -- 13.5 A one-day InfoQ workshop -- 13.6 Summary -- Acknowledgements -- References -- Chapter 14 InfoQ support with R -- 14.1 Introduction -- 14.2 Examples of information quality with R -- 14.3 Components and dimensions of InfoQ and R -- 14.4 Summary -- References -- Chapter 15 InfoQ support with Minitab -- 15.1 Introduction -- 15.2 Components and dimensions of InfoQ and Minitab -- 15.3 Examples of InfoQ with Minitab -- 15.4 Summary -- References -- Chapter 16 InfoQ support with JMP -- 16.1 Introduction -- 16.2 Example 1: Controlling a film deposition process -- 16.3 Example 2: Predicting water quality in the Savannah River Basin -- 16.4 A JMP application to score the InfoQ dimensions -- 16.5 JMP capabilities and InfoQ -- 16.6 Summary -- References -- Index -- EULA -- .

관련분야 신착자료

Deisenroth, Marc Peter (2020)
National Academies of Sciences, Engineering, and Medicine (U.S.) (2020)