X
feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
Type of Medium
Language
Region
Library
Years
Person/Organisation
Subjects(RVK)
Keywords
  • 1
    Online Resource
    Online Resource
    Data analysis : what can be learned from the past 50 years (2011)
    Hoboken, N.J. :Wiley,
    Details
    UID:
    almafu_9959327950802883
    Format: 1 online resource (xiv, 210 pages) : , illustrations
    ISBN: 9781118018248 , 1118018249 , 1118018265 , 9781118018255 , 1118018257 , 9781118018262
    Series Statement: Wiley series in probability and statistics
    Content: "This book explores the many provocative questions concerning the fundamentals of data analysis. It is based on the time-tested experience of one of the gurus of the subject matter. Why should one study data analysis? How should it be taught? What techniques work best, and for whom? How valid are the results? How much data should be tested? Which machine languages should be used, if used at all? Emphasis on apprenticeship (through hands-on case studies) and anecdotes (through real-life applications) are the tools that Peter J. Huber uses in this volume. Concern with specific statistical techniques is not of immediate value; rather, questions of strategy - when to use which technique - are employed. Central to the discussion is an understanding of the significance of massive (or robust) data sets, the implementation of languages, and the use of models. Each is sprinkled with an ample number of examples and case studies. Personal practices, various pitfalls, and existing controversies are presented when applicable. The book serves as an excellent philosophical and historical companion to any present-day text in data analysis, robust statistics, data mining, statistical learning, or computational statistics"--Provided by publisher.
    Content: "This book explores the many provocative questions concerning the fundamentals of data analysis"--
    Note: What Is Data Analysis? -- Strategy Issues in Data Analysis -- Massive Data Sets -- Languages for Data Analysis -- Approximate Models -- Pitfalls -- Create Order in Data -- More Case Studies -- Wiley Series in Probability and Statistics.
    Additional Edition: Print version: Huber, Peter J. Data analysis. Hoboken, N.J. : Wiley, ©2011 ISBN 9781118010648
    Language: English
    Keywords: Electronic books. ; History. ; Electronic books. ; Electronic books. ; History. ; Electronic books. ; History.
    URL: https://onlinelibrary.wiley.com/doi/book/10.1002/9781118018255
    URL: https://onlinelibrary.wiley.com/doi/book/10.1002/9781118018255
    URL: https://onlinelibrary.wiley.com/doi/book/10.1002/9781118018255
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    HU Berlin
    FU Berlin
  • 2
    Book
    Book
    Data analysis : what can be learned from the past 50 years (2011)
    Hoboken, NJ : Wiley
    Details
    UID:
    gbv_637927680
    Format: XIV, 210 S. , graph. Darst. , 25 cm
    ISBN: 9781118010648
    Series Statement: Wiley series in probability and statistics 874
    Content: "This book explores the many provocative questions concerning the fundamentals of data analysis. It is based on the time-tested experience of one of the gurus of the subject matter. Why should one study data analysis? How should it be taught? What techniques work best, and for whom? How valid are the results? How much data should be tested? Which machine languages should be used, if used at all? Emphasis on apprenticeship (through hands-on case studies) and anecdotes (through real-life applications) are the tools that Peter J. Huber uses in this volume. Concern with specific statistical techniques is not of immediate value; rather, questions of strategy - when to use which technique - are employed. Central to the discussion is an understanding of the significance of massive (or robust) data sets, the implementation of languages, and the use of models. Each is sprinkled with an ample number of examples and case studies. Personal practices, various pitfalls, and existing controversies are presented when applicable. The book serves as an excellent philosophical and historical companion to any present-day text in data analysis, robust statistics, data mining, statistical learning, or computational statistics"--
    Note: Includes bibliographical references and index
    Additional Edition: Online-Ausg. Huber, Peter J., 1934 - Data analysis Hoboken, NJ : Wiley, 2011 ISBN 9781118010648
    Additional Edition: Erscheint auch als Online-Ausgabe Data analysis Hoboken : Wiley, 2011 ISBN 9781118018255
    Additional Edition: ISBN 1118018257
    Language: English
    Subjects: Economics , Mathematics
    RVK:
    SK 840
    RVK:
    QH 234
    Keywords: Datenanalyse
    URL: Umschlagbild
    URL: Inhaltsverzeichnis
    URL: Klappentext
    URL: Inhaltstext
    Author information: Huber, Peter J. 1934-
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Book
    Stabi Berlin get availability status
  • 3
    Online Resource
    Online Resource
    Data analysis : what can be learned from the past 50 years (2011)
    Hoboken, N.J. :Wiley,
    Details
    UID:
    edocfu_9961556885102883
    Format: 1 online resource (235 pages)
    Edition: First edition
    ISBN: 1-283-10931-X , 9786613109316 , 1-118-01825-7 , 1-118-01824-9
    Series Statement: Wiley series in probability and statistics
    Content: This book explores the many provocative questions concerning the fundamentals of data analysis. It is based on the time-tested experience of one of the gurus of the subject matter. Why should one study data analysis? How should it be taught? What techniques work best, and for whom? How valid are the results? How much data should be tested? Which machine languages should be used, if used at all? Emphasis on apprenticeship (through hands-on case studies) and anecdotes (through real-life applications) are the tools that Peter J. Huber uses in this volume. Concern with specific statistical techniq
    Note: Description based upon print version of record. , DATA ANALYSIS: What Can Be Learned From the Past 50 Years; CONTENTS; Preface; 1 What is Data Analysis?; 1.1 Tukey's 1962 paper; 1.2 The Path of Statistics; 2 Strategy Issues in Data Analysis; 2.1 Strategy in Data Analysis; 2.2 Philosophical issues; 2.2.1 On the theory of data analysis and its teaching; 2.2.2 Science and data analysis; 2.2.3 Economy of forces; 2.3 Issues of size; 2.4 Strategic planning; 2.4.1 Planning the data collection; 2.4.2 Choice of data and methods; 2.4.3 Systematic and random errors; 2.4.4 Strategic reserves; 2.4.5 Human factors; 2.5 The stages of data analysis , 2.5.1 Inspection2.5.2 Error checking; 2.5.3 Modification; 2.5.4 Comparison; 2.5.5 Modeling and Model fitting; 2.5.6 Simulation; 2.5.7 What-if analyses; 2.5.8 Interpretation; 2.5.9 Presentation of conclusions; 2.6 Tools required for strategy reasons; 2.6.1 Ad hoc programming; 2.6.2 Graphics; 2.6.3 Record keeping; 2.6.4 Creating and keeping order; 3 Massive Data Sets; 3.1 Introduction; 3.2 Disclosure: Personal experiences; 3.3 What is massive? A classification of size; 3.4 Obstacles to scaling; 3.4.1 Human limitations: visualization; 3.4.2 Human - machine interactions , 3.4.3 Storage requirements3.4.4 Computational complexity; 3.4.5 Conclusions; 3.5 On the structure of large data sets; 3.5.1 Types of data; 3.5.2 How do data sets grow?; 3.5.3 On data organization; 3.5.4 Derived data sets; 3.6 Data base management and related issues; 3.6.1 Data archiving; 3.7 The stages of a data analysis; 3.7.1 Planning the data collection; 3.7.2 Actual collection; 3.7.3 Data access; 3.7.4 Initial data checking; 3.7.5 Data analysis proper; 3.7.6 The final product: presentation of arguments and conclusions; 3.8 Examples and some thoughts on strategy; 3.9 Volume reduction , 3.10 Supercomputers and software challenges3.10.1 When do we need a Concorde?; 3.10.2 General Purpose Data Analysis and Supercomputers; 3.10.3 Languages, Programming Environments and Databased Prototyping; 3.11 Summary of conclusions; 4 Languages for Data Analysis; 4.1 Goals and purposes; 4.2 Natural languages and computing languages; 4.2.1 Natural languages; 4.2.2 Batch languages; 4.2.3 Immediate languages; 4.2.4 Language and literature; 4.2.5 Object orientation and related structural issues; 4.2.6 Extremism and compromises, slogans and reality; 4.2.7 Some conclusions; 4.3 Interface issues , 4.3.1 The command line interface4.3.2 The menu interface; 4.3.3 The batch interface and programming environments; 4.3.4 Some personal experiences; 4.4 Miscellaneous issues; 4.4.1 On building blocks; 4.4.2 On the scope of names; 4.4.3 On notation; 4.4.4 Book-keeping problems; 4.5 Requirements for a general purpose immediate language; 5 Approximate Models; 5.1 Models; 5.2 Bayesian modeling; 5.3 Mathematical statistics and approximate models; 5.4 Statistical significance and physical relevance; 5.5 Judicious use of a wrong model; 5.6 Composite models; 5.7 Modeling the length of day , 5.8 The role of simulation , English
    Additional Edition: ISBN 1-118-01826-5
    Additional Edition: ISBN 1-118-01064-7
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    FU Berlin
Nothing or not found what you are looking for? Please check your search query or use the Interlibrary Loan Search.
Did you mean 1118010957?
Did you mean 1118018265?
Did you mean 1118011287?
Close ⊗
This website uses cookies and the analysis tool Matomo. Further information can be found on the KOBV privacy pages