Practical Statistics for Geographers and Earth Scientists - Nigel Walford

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Résumé :

A practice-oriented and accessible introduction to geographical statistics

In the newly revised Second Edition of Practical Statistics for Geographers and Earth Scientists, distinguished researcher Nigel Walford delivers an authoritative and easy-to-follow introduction to the principles and applications of statistical analysis in a geographical context. The book assists students in the development of competence in the statistical procedures necessary to conduct independent investigations, field-work, and related geographical research projects.

The book explains statistical techniques relevant to geographical, geospatial, earth, and environmental data. It employs graphics and mathematical notation for maximum clarity. Guidance is provided on how to formulate research questions to ensure that the correct data is collected for the chosen analysis method.

This new edition incorporates a new section on exploratory spatial analysis and spatial statistics. It also offers:

• A thorough introduction to first principles in the statistical analysis of geographical data, including discussions of the quality, content, collection, and acquisition of geographical data
• In-depth treatments of geographical data exploration, including the taking of statistical measures or quantities, as well as frequency distributions, probability, and hypotheses
• Comprehensive explorations of testing times, including parametric and nonparametric tests
• Insightful discussions of relationship investigation, including correlation and regression, as well as the spatial aspects of geographical data

Perfect for undergraduates pursuing a degree in geography, Practical Statistics for Geographers and Earth Scientists will also be a valuable tool for students in other earth and environmental sciences....

Biographie:

Nigel Walford is Professor of Applied Geographical Information Systems at Kingston University in the United Kingdom....

Sommaire:

Preface to the Second Edition xiii

Acknowledgements xv

About the Companion Website xvii

Section I First Principles 1

1 What's in a Number? 3

1.1 Introduction to Quantitative Analysis 3

1.2 Nature of Numerical Data 7

1.3 Simplifying Mathematical Notation 12

1.4 Introduction to Case Studies and Structure of the Book 16

References 17

Further Reading 17

2 Geographical Data: Quantity and Content 19

2.1 Geographical Data 19

2.2 Populations and Samples 20

2.2.1 Probability Sampling Techniques 23

2.2.2 Subjective Sampling Techniques 35

2.2.3 Closing Comments on Sampling 38

2.3 Specifying Attributes and Variables 39

2.3.1 Geographical Phenomena as Points 42

2.3.2 Geographical Phenomena as Lines 44

2.3.3 Geographical Phenomena as Areas 47

2.3.4 Closing Comments on Attributes and Variables 49

References 50

Further Reading 50

3 Geographical Data: Collection and Acquisition 51

3.1 Originating Data 51

3.2 Collection Methods 53

3.2.1 Field Observation, Measurement and Survey 53

3.2.2 Questionnaire Surveys 57

3.2.2.1 Questionnaire Delivery 57

3.2.2.2 Question Wording 59

3.2.2.3 Questionnaire Structure 60

3.2.2.4 Questionnaire Design 61

3.2.3 Administrative Records and Documents 65

3.2.4 Interviewing, Focus Groups and Audio Recording 68

3.2.5 Crowdsourced Data 72

3.2.6 Remotely Sensed Collection Methods 74

3.2.6.1 Satellite Imagery 76

3.2.6.2 Aerial Photography 78

3.3 Locating Phenomena in Geographical Space 79

References 83

Further Reading 84

Section II Exploring Geographical Data 87

4 Statistical Measures (or Quantities) 89

4.1 Descriptive Statistics 89

4.2 Spatial Descriptive Statistics 91

4.3 Central Tendency 94

4.3.1 Measures for Non-spatial Data 94

4.3.2 Measures for Spatial Data 97

4.3.3 Distance Measures for Spatial Data 106

4.4 Dispersion 110

4.4.1 Measures for Non-spatial Data 110

4.4.2 Measures for Spatial Data 112

4.5 Measures of Skewness and Kurtosis for Non-spatial Data 116

4.6 Closing Comments 120

References 121

Further Reading 121

5 Frequency Distributions, Probability and Hypotheses 123

5.1 Frequency Distributions 123

5.2 Bivariate and Multivariate Frequency Distributions 129

5.3 Estimation of Statistics from Frequency Distributions 136

5.4 Probability 139

5.4.1 Binomial Distribution 142

5.4.2 Poisson Distribution 145

5.4.3 Normal Distribution 147

5.5 Inference and Hypotheses 153

5.6 Connecting Summary Measures, Frequency Distributions and Probability 157

References 158

Further Reading 159

Section III Testing Times 161

6 Parametric Tests 163

6.1 Introduction to Parametric Tests 163

6.2 One Variable and One Sample 165

6.2.1 Comparing a Sample Mean with a Population Mean 166

6.2.2 Comparing Differences Between Pairs of Measurements for a Sample Divided into Two Parts 176

6.3 Two Samples and One Variable 178

6.3.1 Comparing Two Sample Means with Population Means 179

6.3.2 Comparing Two-Sample Variances with Population Variances 183

6.4 Three or More Samples and One Variable 187

6.4.1 Comparing Three or More Sample Means with Population Means 187

6.5 Confidence Intervals 192

6.6 Closing Comments 194

Further Reading 194

7 Non-parametric Tests 197

7.1 Introduction to Non-parametric Tests ...