Practical Statistics for Geographers and Earth Scientists

ISBN-10: 0470849150

ISBN-13: 9780470849156

Edition: 2006

Authors: Nigel Walford

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Description:

A statistics textbook that all students can work through, regardless of their geography or earth science stream degree pathway and their existing mathematical knowledge. The main rationale for the book is to demystify the mathematical component of statistics and to present these techniques in a digestible fashion. This will be achieved through case studies that illustrate the workings of each technique, through photographs and diagrams that help students visualise some of the processes involved and through a clear explanation of how statistical software packages work.
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Book details

List price: $55.00
Copyright year: 2006
Publisher: John Wiley & Sons, Incorporated
Publication date: 1/25/2011
Binding: Paperback
Pages: 440
Size: 6.75" wide x 10.00" long x 1.00" tall
Weight: 1.738
Language: English

Preface
Acknowledgements
Glossary
First principles
What's in a number?
Learning outcomes
Introduction to quantitative analysis
Nature of numerical data
Simplifying mathematical notation
Introduction to case studies and structure of the book
Geographical data: quantity and content
Learning outcomes
Geographical data
Populations and samples
Specifying attributes and variables
Geographical data: collection and acquisition
Learning outcomes
Originating data
Collection methods
Locating phenomena in geographical space
Statistical measures (or quantities)
Learning outcomes
Descriptive statistics
Spatial descriptive statistics
Central tendency
Dispersion
Measures of skewness and kurtosis for nonspatial data
Closing comments
Frequency distributions, probability and hypotheses
Learning outcomes
Frequency distributions
Bivariate and multivariate frequency distributions
Estimation of statistics from frequency distributions
Probability
Inference and hypotheses
Connecting summary measures, frequency distributions and probability
Testing times
Parametric tests
Learning outcomes
Introduction to parametric tests
One variable and one sample
Two samples and one variable
Three or more samples and one variable
Confidence intervals
Closing comments
Nonparametric tests
Learning outcomes
Introduction to nonparametric tests
One variable and one sample
Two samples and one (or more) variable(s)
Multiple samples and/or multiple variables
Closing comments
Forming relationships
Correlation
Learning outcomes
Nature of relationships between variables
Correlation techniques
Concluding remarks
Regression
Learning outcomes
Specification of linear relationships
Bivariate regression
Concluding remarks
Correlation and regression of spatial data
Learning outcomes
Issues with correlation and regression of spatial data
Spatial and temporal autocorrelation
Trend surface analysis
Concluding remarks
References
Further Reading
Index
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