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\"Statistical Methods for Geography\" is the essential introduction for geography students seeking a comprehensive understanding of key statistical concepts and techniques. Now in its fifth edition, this accessible textbook serves as a practical \'statistics 101\' resource, focusing on student learning with clear definitions, illustrative examples, and exercises throughout. It is fully integrated with online self-assessment exercises and video overviews, providing all the necessary tools to achieve full credits in any undergraduate statistics module.
The fifth edition of this bestselling text covers a wide range of topics crucial for geographic analysis. It includes detailed sections on descriptive statistics, probability, inferential statistics, hypothesis testing, sampling, variance, correlation, and regression analysis. Additionally, it explores spatial patterns and introduces methods for spatial data reduction using factor analysis and cluster analysis. These comprehensive topics ensure students gain a well-rounded understanding of statistical methods applicable to geography.
This edition features new examples drawn from physical geography, alongside additional real-world case studies to enhance practical understanding. The in-text and online exercises have been updated to reflect current applications, complemented by downloadable datasets that facilitate hands-on learning. These enhancements make the book an invaluable resource for students aiming to master statistical analysis within the context of geography.
\"Statistical Methods for Geography\" is the only text you\'ll need for undergraduate courses in statistical analysis, statistical methods, and quantitative geography. Its thorough coverage, combined with engaging instructional features, makes it an indispensable guide for students pursuing a solid foundation in geographic statistics.
- Brand: Sage Publishing
- Author: Rogerson, Peter A.
- Genre: Geography
- Format: Student Edition
- Binding: Paperback
- Language: English
- Publication Date: 2020
- Pages: 432
