Practical Statistics for Geographers and Earth Scientists provides an introductory guide to the principles and application of statistical analysis in context. This book helps students to gain the level of competence in statistical procedures necessary for independent investigations, field-work and other projects. The aim is to explain statistical techniques using data relating to relevant geographical, geospatial, earth and environmental science examples, employing graphics as well as mathematical notation for maximum clarity. Advice is given on asking the appropriate preliminary research questions to ensure that the correct data is collected for the chosen statistical analysis method. The book offers a practical guide to making the transition from understanding principles of spatial and non-spatial statistical techniques to planning a series analyses and generating results using statistical and spreadsheet computer software. Learning outcomes included in each chapter International focus Explains the underlying mathematical basis of spatial and non-spatial statistics Provides an geographical, geospatial, earth and environmental science context for the use of statistical methods Written in an accessible, user-friendly style Datasets available on accompanying website at wiley.com/go/Walford

Practical Statistics for Geographers and Earth Scientistsprovides an introductory guide to the principles and application ofstatistical analysis in context. This book helps students to gainthe level of competence in statistical procedures necessary forindependent investigations, field-work and other projects. The aimis to explain statistical techniques using data relating torelevant geographical, geospatial, earth and environmental scienceexamples, employing graphics as well as mathematical notation formaximum clarity. Advice is given on asking the appropriatepreliminary research questions to ensure that the correct data iscollected for the chosen statistical analysis method. The bookoffers a practical guide to making the transition fromunderstanding principles of spatial and non-spatial statisticaltechniques to planning a series analyses and generating resultsusing statistical and spreadsheet computer software.* Learning outcomes included in each chapter* International focus* Explains the underlying mathematical basis of spatial andnon-spatial statistics* Provides an geographical, geospatial, earth and environmentalscience context for the use of statistical methods* Written in an accessible, user-friendly styleDatasets available on accompanying website at href="wiley.com/go/Walford">wiley.com/go/Walford

Preface xiAcknowledgements xiiiGlossary xvSection 1 First principles 11 What's in a number? 3Learning outcomes1.1 Introduction to quantitative analysis 41.2 Nature of numerical data 91.3 Simplifying mathematical notation 141.4 Introduction to case studies and structure of the book 192 Geographical data: quantity and content 21Learning outcomes2.1 Geographical data 212.2 Populations and samples 222.3 Specifying attributes and variables 433 Geographical data: collection and acquisition 57Learning outcomes3.1 Originating data 583.2 Collection methods 593.3 Locating phenomena in geographical space 874 Statistical measures (or quantities) 93Learning outcomes4.1 Descriptive statistics 934.2 Spatial descriptive statistics 964.3 Central tendency 1004.4 Dispersion 1184.5 Measures of skewness and kurtosis for nonspatial data 1244.6 Closing comments 1295 Frequency distributions, probability and hypotheses 131Learning outcomes5.1 Frequency distributions 1325.2 Bivariate and multivariate frequency distributions 1375.3 Estimation of statistics from frequency distributions 1455.4 Probability 1495.5 Inference and hypotheses 1655.6 Connecting summary measures, frequency distributions and probability 169Section 2 Testing times 1736 Parametric tests 175Learning outcomes6.1 Introduction to parametric tests 1766.2 One variable and one sample 1776.3 Two samples and one variable 2016.4 Three or more samples and one variable 2106.5 Confi dence intervals 2166.6 Closing comments 2197 Nonparametric tests 221Learning outcomes7.1 Introduction to nonparametric tests 2227.2 One variable and one sample 2237.3 Two samples and one (or more) variable(s) 2457.4 Multiple samples and/or multiple variables 2567.5 Closing comments 264Section 3 Forming relationships 2658 Correlation 267Learning outcomes8.1 Nature of relationships between variables 2688.2 Correlation techniques 2758.3 Concluding remarks 2989 Regression 299Learning outcomes9.1 Specification of linear relationships 3009.2 Bivariate regression 3029.3 Concluding remarks 33610 Correlation and regression of spatial data 341Learning outcomes10.1 Issues with correlation and regression of spatial data 34210.2 Spatial and temporal autocorrelation 34510.3 Trend surface analysis 37810.4 Concluding remarks 394References 397Further Reading 399Index 403Plate section: Statistical Analysis Planner and Checklist falls between pages 172 and 173