Statistical Methods for Geography
A Student’s Guide
- Peter A Rogerson - University of Buffalo, USA
Now fully integrated with online self-assessment exercises and video navigation, it explains everything required to get full credits for any undergraduate statistics module:
- Descriptive statistics, probability, inferential statistics, hypothesis testing and sampling, variance, correlation, regression analysis, spatial patterns, spatial data reduction using factor analysis and cluster analysis.
- Exercises in the text are complemented with online exercise and prompts that test the understanding of concepts and techniques, additional online exercises review understanding of the entire chapter, relating concepts and techniques.
- Completely revised and updated for accessibility, including new material (on measures of distance, statistical power, sample size selection, and basic probability) with related exercises and downloadable datasets.
Supplements
The website offers a range of interactive teaching and learning materials for both lecturers and students, including:
- Audio slidecasts explaining the key concepts
- Excercises with solutions for both students and instructors
- Datasets: Each dataset utilised in the text is included with a description of its format and fields
In this 4th edition of what is now becoming a classic text, Professor Rogerson provides us with the most up-to-date and comprehensive treatment of basic statistics for geographers. He does so in a very user friendly manner with informative, real-world data sets that bring the statistics to life. This is a book I will certainly use for teaching undergraduate statistics and recommend it very highly. A really useful text for which the author is to be congratulated.
At a time where spatial quantitative methods are of increasing importance to all concerned with geographical analysis, Rogerson’s book is a nicely structured, well explained and up-to-date introduction to and survey of statistical methods in geography and the reasoning behind the techniques.
Statistics has become critically important in contemporary geographical analysis. Statistical literacy is one of the graduate attributes with which universities prepare their geography students. Statistical Methods for Geography - A Student’s Guide by Peter A. Rogerson provides a fundamental and accessible statistics textbook tailored for geography with well-designed illustrations and exercises. It is suitable for students of geography at all levels.
In its previous editions, this book provided an outstanding introduction to statistics for geographers or anyone working with geographical data. The explanations of techniques and the examples and practical exercises are all excellent. This latest edition now incorporates material on a number of new topics such as statistical power and ways of measuring distance, and also includes new and timely example datasets from a variety of geographical locations. Its unique breadth of coverage of statistical ideas and examples make this an excellent choice as a key text for teaching quantitative techniques. I have no hesitation in recommending this book.
This book remains the best available guide for any student seeking to use statistical methods to answer the question, ‘where?’. It provides a lucid, comprehensive and practical introduction that will be used widely across geography, and other social and environmental sciences.
This course book provides basic knowledge about empirical methods and statistical approaches for geography students. This book has a geographical and spatial point of view for general statistical methods. Therefore, this book goes a little bit further than generic statistical books. This textbook starts with generic statistical methods. Subsequently, the main point for geography students is the spatial approach of the book. Therefore, my opinion is that this book is applicable reading for geography students to get familiar with quantitative methods in their own field - in spatial context.
It is a very "student friendly" guide of the basic statistical methods. I really appreciate that the book is also using Excel in few chapters because it is, unfortunately, the most available "statistical" software for students (our university has not got a multi license for SPSS). It is also very valuable that Rogerson's textbook is truly for geographers, dealing with very useful tool of geographically weighted regression.
Level is too advanced for the year one course that I teach.
I am sure that this book provides students with every thing they nee to know in both statics course.
Very nice book but not exactly what I was looking for - still researching
