Last edited by Mugul
Thursday, July 9, 2020 | History

4 edition of Data analysis and infomatics, IV found in the catalog.

Data analysis and infomatics, IV

proceedings of the Fourth International Symposium on Data Analysis and Informatics organised by the Institut national de recherche en informatique et en automatique, Versailles, October 9-11, 1985

by International Symposium on Data Analysis and Informatics (4th 1985 Versailles, France)

  • 396 Want to read
  • 1 Currently reading

Published by Elsevier Science .
Written in English

    Subjects:
  • Mathematical statistics -- Data processing.

  • Edition Notes

    Statementedited by E. Diday ... (et al.).
    ContributionsDiday, E., Institut national de recherche en informatique et en automatique.
    Classifications
    LC ClassificationsQA276.4
    The Physical Object
    Paginationxiii,764p.
    Number of Pages764
    ID Numbers
    Open LibraryOL21433414M
    ISBN 100444700617

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Data analysis and infomatics, IV by International Symposium on Data Analysis and Informatics (4th 1985 Versailles, France) Download PDF EPUB FB2

Get this from a library. Data analysis and informatics, IV: proceedings of the Fourth International Symposium on Data Analysis and Informatics. [E Diday; Institut national de recherche en. The contributions are grouped into seven chapters: 1.

Classification and Clustering, 2. Uncertainty and Fuzziness, 3. Methods of Data Analysis and Applications, 4. Statistical Models and Methods, 5. Bayesian Learning, 6. Conceptual Classification, Knowledge Ordering and Information.

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in Section V of the Handbook we examine data analysis using examples of data from each of the Head Start content areas. We explore examples of how data analysis could be done. We identify and describe trends in data that programs collect.

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DATA ANALYSIS AND RESEARCH FINDINGS INTRODUCTION This chapter describes the analysis of data followed by a discussion of the research findings. The findings relate to the research questions that guided the study. Data were analyzed to identify, describe and explore the relationship between death anxiety.

collected data. It is a messy, ambiguous, time-consuming, creative, and fascinating process. It does not proceed in a linear fashion; it is not neat. Qualitative data analysis is a search for general statements about relationships among categories of data.

data is of limited availability. Therefore, in addition to some contrived examples and some real examples, the majority of the examples in this book are based on simulation of data designed to match real experiments.

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