Statistical Techniques in Geographical Analysis Second Edition Gareth Shaw Department of Geography, University of Exeter and Dennis Wheeler Department of Geography, University of Sunderland The second edition of this widely-used undergraduate textbook is shorter than its predecessor, but now contains a thorough treatment of computational methods. It aims to cover degree students’ needs in statistical methods from their first to final years. Assuming no more than basic secondary or high school mathematics, the authors provide coverage of a range of techniques, from simple descriptive to parametric and non-parametric methods in bivariate and multivariate settings. Almost invariably, each techniques is introduced ‘manually’, followed up by the appropriate application using either the SPSS or MINITAB software packages — the two statistical packages most widely used by geographers. Topics are introduced in an orderly sequence, reinforced by worked examples, so that the book can be equally valuable as part of a teaching scheme, as an aid in distance learning or as an accessible reference source on the different techniques. Fulton textbooks for geography students The Middle East: a Geographical Study, Second Edition Peter Beaumont, Gerald Blake and Malcolm Wagstaff 1-85346-093-1 640 pages Paperback Cities in Space: City as Place David Herbert and Colin Thomas 352 pages 1-85346-109-1 Paperback 1-85346-138-5 Hardback The European City: a Western Perspective, Second Edition David Burtenshaw, Michael Bateman and Gregory Ashworth 1-85346-030-3 324 pages Paperback Retailing: Shopping, Society, Space Larry O’Brien and Frank Harris 1-85346-122-9 160 pages Paperback

Statistical Methods for Geography is the essential introduction for geography students looking to fully understand and apply key statistical concepts and techniques. Now in its fifth edition, this text is an accessible statistics ‘101’ focused on student learning, and includes definitions, examples, and exercises throughout. Fully integrated with online self-assessment exercises and video overviews, it explains everything required to get full credits for any undergraduate statistics module. The fifth edition of this bestselling text includes: · Coverage of descriptive statistics, probability, inferential statistics, hypothesis testing and sampling, variance, correlation, regression analysis, spatial patterns, spatial data reduction using factor analysis and cluster analysis. · New examples from physical geography and additional real-world examples. · Updated in-text and online exercises along with downloadable datasets. This is the only text you’ll need for undergraduate courses in statistical analysis, statistical methods, and quantitative geography.

Statistics Analysis of Geographical Data: An Introduction provides a comprehensive and accessible introduction to the theory and practice of statistical analysis in geography. It covers a wide range of topics including graphical and numerical description of datasets, probability, calculation of confidence intervals, hypothesis testing, collection and analysis of data using analysis of variance and linear regression. Taking a clear and logical approach, this book examines real problems with real data from the geographical literature in order to illustrate the important role that statistics play in geographical investigations. Presented in a clear and accessible manner the book includes recent, relevant examples, designed to enhance the reader’s understanding.

Written for undergraduate geography majors and entry-level graduate students with limited backgrounds in statistical analysis and methods, McGrew and Monroe provide a comprehensive and understandable introduction to statistical methods in a problem-solving framework. Engaging examples and problems are drawn from a variety of topical areas in both human and physical geography and are fully integrated into the text. Without compromising statistical rigor or oversimplifying, the authors stress the importance of written narratives that explain each statistical technique. After introducing basic statistical concepts and terminology, the authors focus on nonspatial and spatial descriptive statistics. They transition to inferential problem solving, including probability, sampling, and estimation, before delving deeper into inferential statistics for geographic problem solving. The final chapters examine the related techniques of correlation and regression. A list of major goals and objectives is included at the end of each chapter, allowing students to monitor their own progress and mastery of geographic statistical materials. An epilogue, offering over 150 geographic situations, gives students a chance to figure out which statistical technique should be used for a particular situation.

Providing a solid foundation for twenty-first-century scientists and engineers, Data Analysis and Statistics for Geography, Environmental Science, and Engineering guides readers in learning quantitative methodology, including how to implement data analysis methods using open-source software. Given the importance of interdisciplinary work in sustain

This book is aimed directly at students of geography, particularly those who lack confidence in manipulating numbers. The aim is not to teach the mathematics behind statistical tests, but to focus on the logic, so that students can choose the most appropriate tests, apply them in the most convenient way and make sense of the results. Introductory chapters explain how to use statistical methods and then the tests are arranged according to the type of data that they require. Diagrams are used to guide students toward the most appropriate tests. The focus is on nonparametric methods that make very few assumptions and are appropriate for the kinds of data that many students will collect. Parametric methods, including Student’s t-tests, correlation and regression are also covered. Although aimed directly at geography students at senior undergraduate and graduate level, this book provides an accessible introduction to a wide range of statistical methods and will be of value to students and researchers in allied disciplines including Earth and environmental science, and the social sciences.