'This book provides students with everything they need to know in both a basic statistics course and also in introductory courses focused on spatial data analysis. It is extremely well-written, well-organised and has plenty of easily understood examples - really the ideal textbook. I recommend it extremely highly' - Stewart Fotheringham, Director, National Centre for Geocomputation National University of Ireland, Maynooth. The Third Edition of this bestselling student favourite 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; and, updated downloadable datasets.

Table of Contents

Preface to the Second Edition Preface to the Third Edition Introduction to Statistical Methods for Geography Descriptive Statistics Probability and Discrete Probability Distributions Continuous Probability Distributions and Probability Models Inferential Statistics: Confidence Intervals, Hypothesis Testing and Sampling Analysis of Variance Correlation Introduction to Regression Analysis More on Regression Spatial Patterns Some Spatial Aspects of Regression Analysis Data Reduction: Factor Analysis and Cluster Analysis Epilogue Appendix A: Statistical Tables Table A.1 Random Digits Table A.2 Normal Distribution Table A.3 Student's t-Distribution Table A.4 Cumulative t-Distribution Table A.5 F-Distribution Table A.6 X2 Distribution Appendix B: Mathematical Conventions and Notation B.1 Mathematical Conventions B.2 Mathematical Notation Appendix C: Review and Extension of Some Probability Theory C.1 Expected Values C.2 Variation of a Random Variable C.3 Covariance of Random Variables

Author Biography

I am Professor of Geography and Biostatistics at the University at Buffalo. My research interests are in the area of demography and population change, epidemiology, spatial statistics, and spatial analysis. My current work is focused upon the development of new methods for the quick detection of newly emergent clusters in geographic data (for example, how does one determine as quickly as possible whether there is a new cluster of crime or disease?).