Statistical methods for geography
Author(s)
Bibliographic Information
Statistical methods for geography
Sage Publications, c2001
- : pbk
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Note
Includes bibliography (p. [229]-232) and index
Description and Table of Contents
Description
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 precis 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
Table of Contents
Introduction to Statistical Analysis in Geography
Probability and Probability Models
Hypothesis Testing and Sampling
Analysis of Variance
Correlation
Introduction to Regression Analysis
More on Regression
Spatial Patterns
Some Spatial Aspects of Regression Analysis
Data Reduction
Factor Analysis and Cluster Analysis
by "Nielsen BookData"
