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2 - Exploratory Spatial Data Analysis Tools and Statistics

Published online by Cambridge University Press:  20 May 2020

George Grekousis
Affiliation:
Sun Yat-Sen University (SYSU), China
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Summary

This chapter deals with

  • The notion of exploratory spatial data analysis

  • The presentation of descriptive statistics

  • Spatial statistics and their importance in analyzing spatial data

  • Analyzing univariate data

  • Simple exploratory spatial data analysis tools such as histograms, boxplots and other visual methods to get a better insight of spatial datasets

  • Bivariate analysis

  • Correlation and pairwise correlation

  • Normalization, rescaling and adjustments

  • An introduction of basic notions of statistical significant tests

  • The importance of hypothesis setting in a spatial context

  • The importance of normal distribution in classic statistics and how it is integrated into spatial analysis

After a thorough study of the theory and lab sections, you will be able to

  • Have a solid knowledge of descriptive statistics

  • Use descriptive statistics for univariate analysis

  • Understand and use exploratory spatial data analysis techniques to map and analyze variables attached to spatial objects

  • Create several plots, link them to maps and identify interesting patterns of data

  • Conduct bivariate analysis, identify whether two variables are linearly related and use plots to further examine their relation

  • Rescale data to make comparisons between variables easier and also allow for better data handling

  • Apply ESDA tools through ArcGIS and GeoDa

Type
Chapter
Information
Spatial Analysis Methods and Practice
Describe – Explore – Explain through GIS
, pp. 59 - 146
Publisher: Cambridge University Press
Print publication year: 2020

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