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Statistical Methods for Geography is a systematic introduction to the essential techniques that all students must understand to complete a module in statistical analysis. It provides an integrated overview of spatial data and spatial data analysis. Key features include: - An applied focus on methods for geographers: the text presents a detailed discussion of regression analysis and autocorrelation - the principal methods of statistical inference used in geography - An introduction to the principles of spatial analysis and spatial patterns, including probability and probability models; hypothesis testing and sampling; analysis of variance; point patterns; and patterns in areal data. The text concludes with an overview of data reduction techniques - Unlike other introductory primers, Statistical Methods for Geography includes self-assessment exercises - with downloadable data sets - at the end of each chapter. The use and application of statistical software - including SPSS - is discussed throughout. Statistical Methods for Geography will be required reading for undergraduate modules in statistical analysis and a useful prcis of techniques for post-graduate students "Peter Rogerson has provided us with an accessible introduction to the main statistical procedures used by geographers, along with valuable illustrations of how these can be applied using SPSS for Windows. As a primer in statistical analysis for geographers it will be widely used and appreciated." - Professor Ron Johnston, School of Geographical Sciences, University of Bristol

Geography --- Spatial analysis (Statistics) --- Analysis, Spatial (Statistics) --- Correlation (Statistics) --- Spatial systems --- Statistical methods --- Mathematics --- 551.02

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The so-called data deluge, along with ever-increasing technological capabilities, tantalizes geographers with exciting opportunities for spatial data analysis. These opportunities come with challenges, because data and technology, alone, cannot address the pressing questions of our world. Spatial analysis, a.k.a. spatial statistics, is a lot more than colourful maps and attractive displays: still relatively underrepresented in the Italian geography, this discipline has grown from a strictly quantitative niche to part of a critical spatial science and continues to stimulate new developments in statistics because, as we know, spatial is special. This book, published in the series “New Geographies. Work Tools”, adds spatial analysis to the Italian geographer’s toolbox. Not a how-to manual, it presents some of the core analytical issues through the redundancy of narrative language and mathematical language. It traces the journey of spatial analysis from its roots in quantitative geography, GIS, and statistics, towards the definition of its own identity and the acceptance of its own relativity and limitations. It discusses the relationship of spatial analysis with GIScience and its efforts to embed critiques within its own discourse, emphasizing the role of theory, the importance of hypothesis testing, and acknowledging the ethics surrounding the use and analysis of data. A few examples illustrate practical implementations, showing the value added by spatial statistics in yielding reliable analyses that can support management decisions. It concludes with a brief outlook on the Italian geographic literature, where spatial analysis – like elsewhere – can play a role in competently accepting today’s opportunities and challenges, in a constructive dialogue within geography as a whole.

Geography --- Geographical information systems (GIS) & remote sensing --- Spatial analysis --- GIS --- spatial statistics --- critical spatial science --- geospatial analytics --- GIScience --- Spatial analysis --- GIS --- spatial statistics --- critical spatial science --- geospatial analytics --- GIScience

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Spatial analysis assists theoretical understanding and empirical testing in the social sciences, and rapidly expanding applications of geographic information technologies have advanced the spatial data-gathering needed for spatial analysis and model making. This much-needed volume covers outstanding examples of spatial thinking in the social sciences, with each chapter showing some aspect of how certain social processes can be understood by analyzing their spatial context. The audience for this work is as trans-disciplinary as its authorship because it contains approaches and methodologies use

Spatial analysis (Statistics) --- Population geography --- Demography --- Human geography --- Analysis, Spatial (Statistics) --- Correlation (Statistics) --- Spatial systems --- Statistical methods. --- Social sciences --- Research.

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Economic geography --- Quantitative methods (economics) --- Spatial analysis (Statistics) --- Analysis, Spatial (Statistics) --- Correlation (Statistics) --- Spatial systems --- Spatial analysis (Statistics). --- METHODES QUANTITATIVES --- SCIENCES SOCIALES

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Geography --- Mathematical statistics --- Spatial analysis (Statistics) --- Mathematics --- Mathematics. --- Spatial analysis (Statistics). --- Analyse spatiale (Statistique) --- Géographie --- Mathématiques. --- Analysis, Spatial (Statistics) --- Correlation (Statistics) --- Spatial systems --- Methodology --- Geography - Mathematics