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2006•Unpublished venueRequires access

TEACHING SPATIAL STATISTICAL TECHNIQUES AND CONCEPTS

Richard Castle

Open publisher page 1 citations

Abstract

The last decade has seen a rapid increase in the use of Geographical Information Systems (GIS) and the analysis of spatial data is an important component of this development. Spatial statistics is a relatively young subject and, although there are useful textbooks on spatial statistics theory, there is virtually no literature on how to teach spatial statistical concepts and techniques. This paper suggests ways of teaching some of spatial statistical analysis without recourse to matrix algebra and vectors. By using the graphical features in Excel it is possible to illustrate and explain the concepts behind the statistical techniques in GIS. The interactive and dynamic features of Excel enable students to investigate the effects of changing the spatial location of the data and to develop an understanding of spatial dependence and its impact on Kriging and regression techniques.

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What this paper is about

The last decade has seen a rapid increase in the use of Geographical Information Systems (GIS) and the analysis of spatial data is an important component of this development. Spatial statistics is a relatively young subject and, although there are useful textbooks on spatial statistics theory, there is virtually no literature on how to teach spatial statistical concepts and techniques. This paper suggests ways of teaching some of spatial statistical analysis without recourse to matrix algebra and vectors. By using the graphical features in Excel it is possible to illustrate and explain the concepts behind the statistical techniques in GIS. The interactive and dynamic features of Excel enable students to investigate the effects of changing the spatial location of the data and to develop an understanding of spatial dependence and its impact on Kriging and regression techniques.

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Available abstract

The last decade has seen a rapid increase in the use of Geographical Information Systems (GIS) and the analysis of spatial data is an important component of this development. Spatial statistics is a relatively young subject and, although there are useful textbooks on spatial statistics theory, there is virtually no literature on how to teach spatial statistical concepts and techniques. This paper suggests ways of teaching some of spatial statistical analysis without recourse to matrix algebra and vectors. By using the graphical features in Excel it is possible to illustrate and explain the concepts behind the statistical techniques in GIS. The interactive and dynamic features of Excel enable students to investigate the effects of changing the spatial location of the data and to develop an understanding of spatial dependence and its impact on Kriging and regression techniques.

Key concepts: Spatial analysis, Computer science, Statistical graphics, Component (thermodynamics), Geographic information system, Statistical analysis, Data mining, Data science

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