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.
This accessible new textbook offers a straightforward introduction to doing spatial statistics. Grounded in real world examples, it shows you how to extend traditional statistical methods for use with spatial data. The book assumes basic mathematical and statistics knowledge but also provides a handy refresher guide, so that you can develop your understanding and progress confidently. It also: · Equips you with the tools to both interpret and apply spatial statistical methods · Engages with the unique considerations that apply when working with geographic data · Helps you build your knowledge of key spatial statistical techniques, such as methods of geographic cluster detection.
Concentrates on both applied demographic and planning techniques which rely upon geographical aspects of population data. Describes methods used to assess the impact of population change on facility demand, school enrollment, changes in product market, transportation and recreation demand forecasting. Applied problems expose students to hands-on planning problems. Questions and solutions use actual data.
A personal history of Peter Wade-Martins archaeological endeavour in Norfolk set within a national context. It covers the writer’s early experiences as a volunteer, the rise of field archaeology as a profession and efforts to conserve archaeological heritage.
Chapters 1 through y present the essential material of plane geometry and can easily be covered in three-unit, one-semester course, perhaps omitting the optional trigonometry section. The additional topics in Chapters 8, 9, and 10 provide enrichment materials and enable the book to be used for a five-unit, one-semester course, or for a two-quarter course. These three chapters are sufficiently independent so that any of them can be used separately.
This accessible new textbook offers a straightforward introduction to doing spatial statistics. Grounded in real world examples, it shows you how to extend traditional statistical methods for use with spatial data. The book assumes basic mathematical and statistics knowledge but also provides a handy refresher guide, so that you can develop your understanding and progress confidently. It also: · Equips you with the tools to both interpret and apply spatial statistical methods · Engages with the unique considerations that apply when working with geographic data · Helps you build your knowledge of key spatial statistical techniques, such as methods of geographic cluster detection.
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.
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.
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