Preface xi Acknowledgements xiii Glossary xv Section 1 First principles 1 1 What's in a number? 3 Learning outcomes 1.1 Introduction to quantitative analysis 4 1.2 Nature of numerical data 9 1.3 Simplifying mathematical notation 14 1.4 Introduction to case studies and structure of the book 19 2 Geographical data: quantity and content 21 Learning outcomes 2.1 Geographical data 21 2.2 Populations and samples 22 2.3 Specifying attributes and variables 43 3 Geographical data: collection and acquisition 57 Learning outcomes 3.

1 Originating data 58 3.2 Collection methods 59 3.3 Locating phenomena in geographical space 87 4 Statistical measures (or quantities) 93 Learning outcomes 4.1 Descriptive statistics 93 4.2 Spatial descriptive statistics 96 4.3 Central tendency 100 4.4 Dispersion 118 4.5 Measures of skewness and kurtosis for nonspatial data 124 4.

6 Closing comments 129 5 Frequency distributions, probability and hypotheses 131 Learning outcomes 5.1 Frequency distributions 132 5.2 Bivariate and multivariate frequency distributions 137 5.3 Estimation of statistics from frequency distributions 145 5.4 Probability 149 5.5 Inference and hypotheses 165 5.6 Connecting summary measures, frequency distributions and probability 169 Section 2 Testing times 173 6 Parametric tests 175 Learning outcomes 6.1 Introduction to parametric tests 176 6.

2 One variable and one sample 177 6.3 Two samples and one variable 201 6.4 Three or more samples and one variable 210 6.5 Confi dence intervals 216 6.6 Closing comments 219 7 Nonparametric tests 221 Learning outcomes 7.1 Introduction to nonparametric tests 222 7.2 One variable and one sample 223 7.3 Two samples and one (or more) variable(s) 245 7.

4 Multiple samples and/or multiple variables 256 7.5 Closing comments 264 Section 3 Forming relationships 265 8 Correlation 267 Learning outcomes 8.1 Nature of relationships between variables 268 8.2 Correlation techniques 275 8.3 Concluding remarks 298 9 Regression 299 Learning outcomes 9.1 Specification of linear relationships 300 9.2 Bivariate regression 302 9.3 Concluding remarks 336 10 Correlation and regression of spatial data 341 Learning outcomes 10.

1 Issues with correlation and regression of spatial data 342 10.2 Spatial and temporal autocorrelation 345 10.3 Trend surface analysis 378 10.4 Concluding remarks 394 References 397 Further Reading 399 Index 403 Plate section: Statistical Analysis Planner and Checklist falls between pages 172 and 173.