Statistical Methods For Geographers
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Statistical Methods for Geographers
A textbook for advanced undergraduate/first year graduate level courses in statistical methods in geography. Presents methods useful in research design, hypothesis testing, and analyzing spatial and functional relationships. Introduces basic statistical terms and techniques for displaying and describing distributions, and covers a range of working methods including probability and sampling, simple linear regression, extensions of the simple linear model to multiple regression and its assumptions, stepwise logit regression, and canonical and discriminant analysis.
Statistical Methods and the Geographer
First published in 1978. For the non-mathematician, however, even the simpler introductory books on statistics often raise considerable problems. In this second edition First, some attention has been given to the problem of the transformation of data in order to reinforce the appreciation of the need for normally-distributed data for the use of so many techniques. Secondly, the use of probability paper, at least in simple terms, has been introduced to illustrate the ways in which the labour of probability assessments can be circumvented. Thirdly, radical changes have been made, plus considerable expansion added, to the theme of non-parametric testing, to provide a more systematic approach to what is a most important group of possible techniques for geographers. Fourthly, change and expansion are also reflected in the sections on correlation and regression, including some simple consideration of curvilinear relationships and the presentation of computational techniques more geared to the use of desk calculators rather than long-hand methods. Finally, the bibliography has also been expanded, to incorporate a wider range of books on techniques and a selection of research papers using such techniques in a geographical (or near-geographical) context.
Statistical Methods for Geography
Statistical Methods for Geography is a systematic introduction to the essential techniques that all students must understand to complete a module in statistical analysis. It provides an integrated overview of spatial data and spatial data analysis. Key features include: - An applied focus on methods for geographers: the text presents a detailed discussion of regression analysis and autocorrelation - the principal methods of statistical inference used in geography. - An introduction to the principles of spatial analysis and spatial patterns, including probability and probability models; hypothesis testing and sampling; analysis of variance; point patterns; and patterns in areal data.