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Statistical Analysis of Geographical Data

Statistical Analysis of Geographical Data
Author: Simon James Dadson
Publisher: John Wiley & Sons
Total Pages: 252
Release: 2017-03-08
Genre: Science
ISBN: 1118525140

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Statistics Analysis of Geographical Data: An Introduction provides a comprehensive and accessible introduction to the theory and practice of statistical analysis in geography. It covers a wide range of topics including graphical and numerical description of datasets, probability, calculation of confidence intervals, hypothesis testing, collection and analysis of data using analysis of variance and linear regression. Taking a clear and logical approach, this book examines real problems with real data from the geographical literature in order to illustrate the important role that statistics play in geographical investigations. Presented in a clear and accessible manner the book includes recent, relevant examples, designed to enhance the reader’s understanding.


Statistical Analysis of Geographical Data

Statistical Analysis of Geographical Data
Author: Simon James Dadson
Publisher: John Wiley & Sons
Total Pages: 276
Release: 2017-05-08
Genre: Science
ISBN: 0470977043

Download Statistical Analysis of Geographical Data Book in PDF, ePub and Kindle

Statistics Analysis of Geographical Data: An Introduction provides a comprehensive and accessible introduction to the theory and practice of statistical analysis in geography. It covers a wide range of topics including graphical and numerical description of datasets, probability, calculation of confidence intervals, hypothesis testing, collection and analysis of data using analysis of variance and linear regression. Taking a clear and logical approach, this book examines real problems with real data from the geographical literature in order to illustrate the important role that statistics play in geographical investigations. Presented in a clear and accessible manner the book includes recent, relevant examples, designed to enhance the reader’s understanding.


Statistical Analysis of Geographical Data

Statistical Analysis of Geographical Data
Author: Simon James Dadson
Publisher: John Wiley & Sons
Total Pages: 264
Release: 2017-05-08
Genre: Science
ISBN: 0470977035

Download Statistical Analysis of Geographical Data Book in PDF, ePub and Kindle

Statistics Analysis of Geographical Data: An Introduction provides a comprehensive and accessible introduction to the theory and practice of statistical analysis in geography. It covers a wide range of topics including graphical and numerical description of datasets, probability, calculation of confidence intervals, hypothesis testing, collection and analysis of data using analysis of variance and linear regression. Taking a clear and logical approach, this book examines real problems with real data from the geographical literature in order to illustrate the important role that statistics play in geographical investigations. Presented in a clear and accessible manner the book includes recent, relevant examples, designed to enhance the reader’s understanding.


Statistical Analysis in Geography

Statistical Analysis in Geography
Author: Leslie J. King
Publisher: Englewood Cliffs, N.J. : Prentice-Hall
Total Pages: 312
Release: 1969
Genre: Mathematics
ISBN:

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Geographical Data Analysis

Geographical Data Analysis
Author: Nigel Walford
Publisher: John Wiley & Sons
Total Pages: 472
Release: 1995-07-05
Genre: Business & Economics
ISBN:

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It is increasingly important for the earth science student to appreciate that the acquisition of skills in statistics and computerised data analysis is as much part of modern geography as work in the field, laboratory or library. In this respect, Geographical Data Analysis aims to link the use of statistical techniques by means of computer software, to the acquisition of geographical-knowledge and the scientific method of enquiry. The book has three objectives: to explain basic statistical techniques and demonstrate their application to quantitative geography; to equip students with the knowledge and skills necessary for carrying out research projects; and to make the link between statistical analysis and the substantive topics taught as part of a geography course. An important innovative feature of the book is its project-orientated approach, which utilises exemplar projects drawn from human and physical geography. Each exemplar project shows the progress from the conception of the initial research through to the formulation of tentative hypotheses and the subsequent statistical analysis. The projects exemplify both primary and secondary methods for collecting geographical data, with the computer-based application of a wide range of statistical techniques. Thus, these projects allow discussion of sample design, data collection and computerisation, and a selection of appropriate statistical techniques. As such, Geographical Data Analysis integrates quantitative and geographical methodologies and provides a thorough understanding of basic statistical techniques for the undergraduate geography student; it will be of use from first year through to final degree dissertations.


Geographical Data Science and Spatial Data Analysis

Geographical Data Science and Spatial Data Analysis
Author: Lex Comber
Publisher: SAGE
Total Pages: 460
Release: 2020-12-02
Genre: Science
ISBN: 1526485435

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We are in an age of big data where all of our everyday interactions and transactions generate data. Much of this data is spatial – it is collected some-where – and identifying analytical insight from trends and patterns in these increasing rich digital footprints presents a number of challenges. Whilst other books describe different flavours of Data Analytics in R and other programming languages, there are none that consider Spatial Data (i.e. the location attached to data), or that consider issues of inference, linking Big Data, Geography, GIS, Mapping and Spatial Analytics. This is a ‘learning by doing’ textbook, building on the previous book by the same authors, An Introduction to R for Spatial Analysis and Mapping. It details the theoretical issues in analyses of Big Spatial Data and developing practical skills in the reader for addressing these with confidence.


Statistical Analysis with ArcView GIS

Statistical Analysis with ArcView GIS
Author: Jay Lee
Publisher: John Wiley & Sons
Total Pages: 205
Release: 2001-05-16
Genre: Science
ISBN: 047143776X

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Statistical analysis of geographic data has been greatly enhanced in recent years with the advent of Geographical Information Systems (GIS) software. Yet GIS users have struggles to synchronize their applications of spatial information with practical, quantitative statistics. ArcView, one of the most powerful GIS-compatible systems, has become the most popular software among geographers precisely because of its capacity for spatial-quantitative synthesis. Now geographers Jay Lee and David Wong have produced the first handbook for applied ArcView use, bringing the theoretical underpinnings of classical statistics into the earth science environment. Employing points, lines, and polygons to model real-world geographic forms, this easy-to-use resource provides geographers with a valuable bridge between theory and the software necessary to apply it. It contains sections on point distribution, point pattern analysis, linear features, network analysis, and spatial autocorrelation analysis. Statistical Analysis with ArcView GIS also features: Examples that show steps of statistical calculations-as well as ways to interpret the results. More than 100 illustrations, including statistical charts, maps, and ArcView screen captures. Helpful end-of-chapter references. Suitable for professionals as well as students of geography, this book is an important tool for anyone involved in the statistical analysis of GIS data.


Applied Spatial Data Analysis with R

Applied Spatial Data Analysis with R
Author: Roger S. Bivand
Publisher: Springer Science & Business Media
Total Pages: 414
Release: 2013-06-21
Genre: Medical
ISBN: 1461476186

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Applied Spatial Data Analysis with R, second edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS and the handling of spatio-temporal data. The second part showcases more specialised kinds of spatial data analysis, including spatial point pattern analysis, interpolation and geostatistics, areal data analysis and disease mapping. The coverage of methods of spatial data analysis ranges from standard techniques to new developments, and the examples used are largely taken from the spatial statistics literature. All the examples can be run using R contributed packages available from the CRAN website, with code and additional data sets from the book's own website. Compared to the first edition, the second edition covers the more systematic approach towards handling spatial data in R, as well as a number of important and widely used CRAN packages that have appeared since the first edition. This book will be of interest to researchers who intend to use R to handle, visualise, and analyse spatial data. It will also be of interest to spatial data analysts who do not use R, but who are interested in practical aspects of implementing software for spatial data analysis. It is a suitable companion book for introductory spatial statistics courses and for applied methods courses in a wide range of subjects using spatial data, including human and physical geography, geographical information science and geoinformatics, the environmental sciences, ecology, public health and disease control, economics, public administration and political science. The book has a website where complete code examples, data sets, and other support material may be found: http://www.asdar-book.org. The authors have taken part in writing and maintaining software for spatial data handling and analysis with R in concert since 2003.