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 précis of techniques for post-graduate students.