Statistical Analysis of Geographic Information with ArcView GIS and ArcGIS by David W. S., Lee, Jay Wong - used book

EAN (ISBN-13): 9780471468998
ISBN (ISBN-10): 0471468991
Hardcover
Publishing year: 2005
Publisher: Wiley
464 Pages
Weight: 0,812 kg
Language: eng/Englisch

Book in our database since 2007-05-20T02:19:03+01:00 (London)
Detail page last modified on 2024-01-06T12:42:10+00:00 (London)
ISBN/EAN: 9780471468998

ISBN - alternate spelling:
0-471-46899-1, 978-0-471-46899-8
Alternate spelling and related search-keywords:
Book author: wong lee, david lee, may wong, lee john
Book title: gis, arcgis arcview geodatabase getting lineare programmierung, getting know arcgis, statistical analysis

---

Information from Publisher

Author: Jay Lee; David W. S. Wong
Title: Statistical Analysis of Geographic Information with ArcView GIS and ArcGIS
Publisher: John Wiley & Sons
464 Pages
Publishing year: 2005-11-11
Weight: 0,858 kg
Language: English
145,00 € (DE)
No longer receiving updates
165mm x 239mm x 31mm

BB; gebunden; Hardcover, Softcover / Geowissenschaften/Geografie; Geographische Informationssysteme (GIS) und Fernerkundung; Statistics; Geographie; Statistik; Geoinformationssystem; Geography; GIS, Fernerkundung u. Kartographie; GIS, Remote Sensing & Cartography; GIS, Fernerkundung u. Kartographie; Allg. Statistik; Kartographie, Kartierung

Preface. Introduction. 1. 1 Why Statistics and Sampling? 1.2 What is so Special about Spatial Data? 1.3 Spatial Data and the Needs For Spatial Analysis/Statistics. 1.4 Fundamentals in Spatial Analysis and Statistics. 1.5 ArcView Notes - Data Model and Examples. 1.6 References Cited. 1.7 Exercises. PART I. CLASSICAL STATISTICS. Distribution Descriptors: One Variable (Univariate). 2.1 Measures of Central Tendency. 2.2 Measures of Dispersion. 2.3 ArcView Examples. 2.4 Higher Moments Statistics. 2.5 ArcView Examples. 2.6 Application Example. 2.7 Summary. 2.8 References Cited. 2.9 Exercises. Relationship Descriptors: Two Variables (Bivariate). 3.1 Correlation Analysis. 3.2 Correlation: Nominal Scale. 3.3 Correlation: Ordinal Scale. 3.4 Correlation: Interval / Ratio Scale. 3.5 Trend Analysis. 3.6 ArcView Notes. 3.7 Application Examples. 3.8 Reference Cited. 3.9 Exercises. Hypothesis Testers. 4.1 Probability Concepts. 4.2 Probability Functions. 4.3 Central Limit Theorem and Confidence Intervals. 4.4 Hypothesis Testing. 4.5 Parametric Test Statistics. 4.6 Difference in Means. 4.7 Difference between a mean and a fixed value. 4.8 Significance of Pearson's correlation coefficient. 4.9 Significance of Regression Parameters. 4.10 Testing Non-Parametric Statistics: Chi-Square Statistics, Chi². 4.11 Spearman's Rank Coefficient. 4.12 Kolmogorov-Smirnov Test. 4.13 Summary. 4.14 Reference used in this chapter. 4.15 Exercises. PART II. SPATIAL STATISTICS. Point Pattern Descriptors. 5.1 The Nature of Point Features. 5.2 Central Tendency of Point Distributions. 5.3 Dispersion and Orientation of Point Distributions. 5.4 ArcView Notes. 5.5 Application Examples. 5.6 References Cited. 5.7 Exercises. Point Pattern Analyzers. Scale and Extent. Quadrat Analysis. 6.3 Ordered Neighbor Analysis. 6.4 K-Function. 6.5 Spatial Autocorrelation of Points. 6.6 Application Examples. 6.7 References Cited. 6.8 Exercises. Line Pattern Analyzers. 7.1 The Nature of Linear Features: Vectors and Networks. 7.2 Characteristics and Attributes of Linear Features. 7.3. Directional Statistics. 7.4 Network Analysis. 7.5 Application Examples. 7.6 References Cited. 7.7 Exercises. Polygon Pattern Analyzers. 8.1 Introduction. 8.2 Spatial Relationships. 8.3 Spatial Dependency. 8.4 Spatial Weights Matrices. 8.5 Spatial Autocorrelation Statistics and Notations. 8.6 Joint Count Statistics. (** modify the sections in the original manuscript **). 8.7 Global Statistics. 8.8 Local Spatial Autocorrelation Statistics. 8.9 Moran Scatterplot. 8.10 ArcView Example 8.4: Local Spatial Autocorrelation Statistics and Moran Scatterplot. 8.11 Bivariate Spatial Autocorrelation. 8.12 Application Examples. 8.13 Summary. 8.14 References Cited. 8.15 Exercises.