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.

This text provides a systematic introduction to the essential techniques that all students must understand to complete a module in statistical analysis. The book provides an overview of spatial data and spatial data analysis.

A textbook for advanced undergraduate/first year graduate level courses in statistical methods in geography. Presents methods useful in research design, hypothesis testing, and analyzing spatial and functional relationships. Introduces basic statistical terms and techniques for displaying and describing distributions, and covers a range of working methods including probability and sampling, simple linear regression, extensions of the simple linear model to multiple regression and its assumptions, stepwise logit regression, and canonical and discriminant analysis.

The Third Edition of this bestselling student favorite has again been revised and updated to provide an expert introduction to the principal methods and techniques needed to understand a statistics module. Features new to this edition include: further introductory material; updated exercises and illustrative examples; updated downloadable datasets Statistical Methods is required reading for undergraduate modules in statistical analysis, statistical methods, and quantitative geography.

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.

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.

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

Statistics in Geography has established itself as the best introductory textbook on the subject: the author makes statistical concepts and techniques intellible and their applications in a wide variety of problems comprehensible, even exciting. The main feature of this much-awaited new edition is a set of 17 computer programs (with sample outputs) that cover nearly all the statistical techniques described. These have been carefully written to be user-friendly in an elementary subset of Basic to make them simple to implement on most micro computers. This means students can be more adventurous in their applications and interpretations of statistical techniques. The author has, at the same time, retained all the worked examples in the book so that the reader can gain insight into the logic of the methds by working through them by hand. These, together with problems of various levels of complexity plus comprehensive answers at the back of the book, provide the student with a clear and thorough understanding of both the methods and their potential applications.

Geodemographic classification is ‘big business’ in the marketing and service sector industries, and in public policy there has also been a resurgence of interest in neighbourhood initiatives and targeting. As an increasing number of professionals realise the potential of geographic analysis for their business or organisation, there exists a timely gap in the market for a focussed book on geodemographics and GIS. Geodemographics: neighbourhood targeting and GIS provides both an introduction to and overview of the methods, theory and classification techniques that provide the foundation of neighbourhood analysis and commercial geodemographic products. Particular focus is given to the presentation and use of neighbourhood classification in GIS. Authored by leading marketing professionals and a prominent academic, this book presents methods, theory and classification techniques in a reader-friendly manner Supported by private and public sector case studies and vignettes The applied ‘how to’ sections will specifically appeal to the intended audience at work in business and service planning Includes information on the recent UK and US Census products and resulting neighbourhood classifications