Practical Statistics for Geographers and Earth Scientists

ISBN-13: 9780470849156 / Angielski / Miękka / 2011 / 440 str.

Nigel Walford

Opis

Practical Statistics for Geographers and Earth Scientists is a text that all students can work through, regardless of their geography or earth science stream degree pathway and their existing mathematical knowledge.

Recenzje

Overall, this is potentially a very useful, reader–friendly book for its target audience.   (Soil Use and Management, 1 December 2013)

"Designed for students with all levels of math background, this book helps take the angst out of the mathematical part of statistics, and encourages students to gain the competence in statistical procedures needed for independent investigations, fieldwork, and other projects." (Booknews, 1 June 2011)

 

Spis treści

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

Blurb

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 www.wiley.com/go/Walford