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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.
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.
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.
Presents the full-text, electronic version of the "1996 Statistical Abstract of the United States," published by the United States Bureau of the Census located in Suitland, Maryland. Notes that the document is entirely in PDF format and the user's browser must have an application such as Adobe Acrobat Reader in order to download and read the document. Includes statistics on the population, health, education, law enforcement, geography, travel, elections, finances and employment, national defense, prices, income, business, communications, energy, science, transportation, agriculture, national resources, housing, domestic trade, foreign commerce, and other items.
Introduces the techniques and concepts of statistics in human and physical geography. This book explains not only how to apply quantitative tools but also why and how they work. It helps students gain important skills for utilizing conventional and spatial statistics in their own research, as well as for critically evaluating the work of others.
'This book provides students with everything they need to know in both a basic statistics course and also in introductory courses focused on spatial data analysis. It is extremely well-written, well-organised and has plenty of easily understood examples - really the ideal textbook. I recommend it extremely highly' - Stewart Fotheringham, Director, National Centre for Geocomputation National University of Ireland Maynooth The Third Edition of this bestselling student favourite 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
The fourth edition of An Introduction to Statistical Problem Solving in Geography continues its standing as the definitive introduction to statistics and quantitative analysis in geography. Assuming no reader background in statistics, the authors lay out the proper role of statistical analysis and methods in human and physical geography. They delve into the calculation of descriptive summaries and graphics to explain geographic patterns and use inferential statistics (parametric and nonparametric) to test for differences (t-tests, ANOVA), relationships (regression and correlation), and spatial statistics (point and area patterns, spatial autocorrelation). This edition introduces more advanced topics, including logistic regression, two-factor ANOVA, and spatial estimation (inverse distance weighting, Kriging). Many chapters also include thought-provoking discussions of statistical concepts as they relate to the COVID-19 pandemic. Maintaining an exploratory and investigative approach throughout, the authors provide readers with real-world geographic issues and more than 50 map examples. Concepts are explained clearly and narratively without oversimplification. Each chapter concludes with a list of major goals and objectives. An epilogue offers over 150 open-ended geographic situations, inviting students to apply their new statistical skills to solve problems currently affecting our world.
Geographical Weighted Regression (GWR) is a new local modelling technique for analysing spatial analysis. This technique allows local as opposed to global models of relationships to be measured and mapped. This is the first and only book on this technique, offering comprehensive coverage on this new 'hot' topic in spatial analysis. * Provides step-by-step examples of how to use the GWR model using data sets and examples on issues such as house price determinants, educational attainment levels and school performance statistics * Contains a broad discussion of and basic concepts on GWR through to ideas on statistical inference for GWR models * uniquely features accompanying author-written software that allows users to undertake sophisticated and complex forms of GWR within a user-friendly, Windows-based, front-end (see book for details).
Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and; * expanded power and sample size tables for multiple regression/correlation.