Geography students need a solid introduction to the variety of ways in which statistical procedures are used to explore and to solve realistic geographic problems. This book is designed to provide a comprehensive and understandable introduction to statistical methods in a practical, problem solving framework. Students who use this text in a spatial analysis or statistical methods course will acquire a well-grounded foundation and feel comfortable in applying statistical techniques in research problems or situations that they might encounter in their subsequent geographic education and careers.
This book is targeted for undergraduate geography majors and beginning graduate students who do not have a strong background in statistical approaches to geographic problem solving.
"synopsis" may belong to another edition of this title.
The level has been reduced where appropriate, especially in the later chapters.
Real world examples and problems are drawn from a wide vareity of topical areas in both human and physical geography. The geographic problems are also drawn from various spatial levels, ranging from local to international.
Continuing emphasis on the use of spatial statistics.
The authors use a flexible, exploratory approach that emphasizes real world problem solving and the p-value method of statistical testing.
A list of major goals and objectives has been added at the end of every chapter.
Throughout the book, there is a greater emphasis on geography. For example, as a technique is introduced there is more detailed and student-friendly discussion about the geographic applications of the technique, with more written narrative examples. This is not to say there is less math and statistics, but rather that there is more supportive written narrative material throughout the text to help the statistics-phobic geography student.
A new "Epilogue Chapter" has been added. This closing chapter contains a lengthy set (over 100) of geographic situations.
Many new examples throughout the text, particularly in the chapters dealing with inferential techniques. Basically, the material in the old chapters 9, 10, and 11 example problems has been dramatically redone and improved.
"About this title" may belong to another edition of this title.
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