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Spatial Data Analysis

Spatial Data Analysis
Theory and Practice

$84.99 (P)

  • Date Published: June 2003
  • availability: Available
  • format: Paperback
  • isbn: 9780521774376

$ 84.99 (P)
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About the Authors
  • Are there geographic clusters of disease cases, or hotspots of crime? Can the geography of air quality be matched to where people hospitalized for respiratory complaints actually live? Spatial data is data about the world where the attribute of interest and its location on the earth's surface are recorded. This comprehensive overview of the subject shows how the above questions can be tackled. It is written for students and researchers in geography, economics, social science, the environmental sciences and statistics.

    • Provides an extensive treatment of the scientific and policy context for using spatial data analysis
    • Complete overview - from fundamental problems of representing the geographical world to how to explore and model spatial data
    • Clear enough for many undergraduates to get a firm grasp on the subject whilst containing enough challenging material to allow graduate students to get a strong understanding of the field
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    Product details

    • Date Published: June 2003
    • format: Paperback
    • isbn: 9780521774376
    • length: 454 pages
    • dimensions: 244 x 170 x 23 mm
    • weight: 0.75kg
    • contains: 88 b/w illus. 33 tables
    • availability: Available
  • Table of Contents

    Preface
    Readership
    Acknowledgements
    Introduction
    Part I. The Context for Spatial Data Analysis:
    1. Spatial data analysis: scientific and policy context
    2. The nature of spatial data
    Part II. Spatial Data: Obtaining Data And Quality Issues:
    3. Obtaining spatial data through sampling
    4. Data quality: implications for spatial data analysis
    Part III. The Exploratory Analysis of Spatial Data:
    5. Exploratory analysis of spatial data
    6. Exploratory spatial data analysis: visualisation methods
    7. Exploratory spatial data analysis: numerical methods
    Part IV. Hypothesis Testing in the Presence of Spatial Autocorrelation:
    8. Hypothesis testing in the presence of spatial dependence
    Part V. Modeling Spatial Data:
    9. Models for the statistical analysis of spatial data
    10. Statistical modeling of spatial variation: descriptive modeling
    11. Statistical modeling of spatial variation: explanatory modeling
    Appendices
    References
    Index.

  • Author

    Robert Haining, University of Cambridge
    Robert Haining is Professor of Human Geography at the University of Cambridge.

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