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Statistical Methods For Geography

Author: Peter A Rogerson
Publisher: SAGE
ISBN: 1473911109
Size: 71.28 MB
Format: PDF, ePub, Docs
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How do beginning students of statistics for geography learn to fully understand the key concepts and apply the principal techniques? This text, now in its Fourth Edition, provides exactly that resource. Accessibly written, and focussed on student learning, it’s a statistics 101 that includes definitions, examples, and exercise throughout. Now fully integrated with online self-assessment exercises and video navigation, it explains everything required to get full credits for any undergraduate statistics module: Descriptive statistics, probability, inferential statistics, hypothesis testing and sampling, variance, correlation, regression analysis, spatial patterns, spatial data reduction using factor analysis and cluster analysis. Exercises in the text are complemented with online exercise and prompts that test the understanding of concepts and techniques, additional online exercises review understanding of the entire chapter, relating concepts and techniques. Completely revised and updated for accessibility, including new material (on measures of distance, statistical power, sample size selection, and basic probability) with related exercises and downloadable datasets. It is the only text required for undergraduate modules in statistical analysis, statistical methods, and quantitative geography.

Statistical Methods For Geography A Students Guide

Author: CTI Reviews
Publisher: Cram101 Textbook Reviews
ISBN: 1478447354
Size: 10.75 MB
Format: PDF, Mobi
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Facts101 is your complete guide to Statistical Methods for Geography, A Students Guide. In this book, you will learn topics such as as those in your book plus much more. With key features such as key terms, people and places, Facts101 gives you all the information you need to prepare for your next exam. Our practice tests are specific to the textbook and we have designed tools to make the most of your limited study time.

Key Methods In Geography

Author: Nicholas Clifford
Publisher: SAGE
ISBN: 9781446243633
Size: 12.15 MB
Format: PDF, ePub, Docs
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"Its range is far broader than the majority of methods texts, being concerned with both human and physical geography... Given the seriousness with which Key Methods in Geography approaches all aspects of research, it will continue to find wide favour among undergraduate geographers." - Times Higher Education Textbook Guide "All geographers, whatever their interest, need to do research. This book will help them get started in the best possible way, with thoughtful advice on everything from project design, through choice of methods, to data analysis and presentation. The editors have assembled an impressive array of authors, all experts in their chosen field." - Tim Burt, University of Durham "Excellent book. Valuable teaching aid. Well written and covers a wide range of methods thoroughly." - Sue Rodway-Dyer, Exeter University "This is an excellent book and deals with a number of topics (which I teach) outside of the tutorial module where it is a recommended text for geographers. A very useful textbook throughout a 3 year Geography programme." - Ian Harris, Bangor University Key Methods in Geography is an introduction to the principal methodological issues involved in the collection, analysis and presentation of geographical information. It is unique in the reference literature for providing an overview of qualitative and quantitative methods for human and physical geography. An accessible primer, it will be used by students as a reference throughout their degree, on all issues from research design to presentation. This second edition has been fully revised and updated and includes new chapters on internet mediated research, diaries as a research method, making observations and measurements in the field, and the analysis of natural systems. Organized into four sections: Getting Started in Geographical Research; Generating and Working with Data in Human Geography; Generating and Working with Data in Physical Geography; Representing and Interpreting Geographical Data; each chapter comprises: A short definition A summary of the principal arguments A substantive 5,000-word discussion Use of real-life examples Annotated notes for further reading. The teaching of research methods is integral to all geography courses: Key Methods in Geography, 2nd Edition explains all of the key methods with which geography undergraduates must be conversant.

Practical Statistics For Geographers And Earth Scientists

Author: Nigel Walford
Publisher: John Wiley & Sons
ISBN: 1119957028
Size: 48.47 MB
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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

Simple Statistical Tests For Geography

Author: Danny McCarroll
Publisher: CRC Press
ISBN: 1498758940
Size: 43.15 MB
Format: PDF, Kindle
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This book is aimed directly at students of geography, particularly those who lack confidence in manipulating numbers. The aim is not to teach the mathematics behind statistical tests, but to focus on the logic, so that students can choose the most appropriate tests, apply them in the most convenient way and make sense of the results. Introductory chapters explain how to use statistical methods and then the tests are arranged according to the type of data that they require. Diagrams are used to guide students toward the most appropriate tests. The focus is on nonparametric methods that make very few assumptions and are appropriate for the kinds of data that many students will collect. Parametric methods, including Student’s t-tests, correlation and regression are also covered. Although aimed directly at geography students at senior undergraduate and graduate level, this book provides an accessible introduction to a wide range of statistical methods and will be of value to students and researchers in allied disciplines including Earth and environmental science, and the social sciences.

Spss 16

Author: Achim Bühl
Publisher: Pearson Deutschland GmbH
ISBN: 9783827373328
Size: 68.44 MB
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Die Standardeinführung für SPSS ist auf der Basis zahlreicher neuer Datensätze für die Version 16 vollständig überarbeitet und erweitert worden. Ausgehend von Problemstellungen aus der Praxis wird gezeigt, wie Sie mit SPSS arbeiten können. Die Beispiele basieren meist auf Fallstudien und sind vor allem dem sozialwissenschaftlichen und dem psychologisch-medizinischen Bereich entnommen. Der Autor beschreibt ausführlich den kompletten statistischen Inhalt der Module Base, Regression Models und Advanced Models. In der 11. Auflage des Werks nimmt erstmals auch die Korrespondenzanalyse einen breiten Raum ein; ein Verfahren, das immer häufiger eingesetzt wird und Zusammenhänge von Variablen optisch als Punkte eines geometrischen Raums aufbereitet.

Wahrscheinlichkeitstheorie Und Stochastische Prozesse

Author: Michael Mürmann
Publisher: Springer-Verlag
ISBN: 364238160X
Size: 78.16 MB
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Dieses Lehrbuch beschäftigt sich mit den zentralen Gebieten einer maßtheoretisch orientierten Wahrscheinlichkeitstheorie im Umfang einer zweisemestrigen Vorlesung. Nach den Grundlagen werden Grenzwertsätze und schwache Konvergenz behandelt. Es folgt die Darstellung und Betrachtung der stochastischen Abhängigkeit durch die bedingte Erwartung, die mit der Radon-Nikodym-Ableitung realisiert wird. Sie wird angewandt auf die Theorie der stochastischen Prozesse, die nach der allgemeinen Konstruktion aus der Untersuchung von Martingalen und Markov-Prozessen besteht. Neu in einem Lehrbuch über allgemeine Wahrscheinlichkeitstheorie ist eine Einführung in die stochastische Analysis von Semimartingalen auf der Grundlage einer geeigneten Stetigkeitsbedingung mit Anwendungen auf die Theorie der Finanzmärkte. Das Buch enthält zahlreiche Übungen, teilweise mit Lösungen. Neben der Theorie vertiefen Anmerkungen, besonders zu mathematischen Modellen für Phänomene der Realität, das Verständnis.​

Data Analysis And Statistics For Geography Environmental Science And Engineering

Author: Miguel F. Acevedo
Publisher: CRC Press
ISBN: 1466592214
Size: 31.15 MB
Format: PDF
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Providing a solid foundation for twenty-first-century scientists and engineers, Data Analysis and Statistics for Geography, Environmental Science, and Engineering guides readers in learning quantitative methodology, including how to implement data analysis methods using open-source software. Given the importance of interdisciplinary work in sustainability, the book brings together principles of statistics and probability, multivariate analysis, and spatial analysis methods applicable across a variety of science and engineering disciplines. Learn How to Use a Variety of Data Analysis and Statistics Methods Based on the author’s many years of teaching graduate and undergraduate students, this textbook emphasizes hands-on learning. Organized into two parts, it allows greater flexibility using the material in various countries and types of curricula. The first part covers probability, random variables and inferential statistics, applications of regression, time series analysis, and analysis of spatial point patterns. The second part uses matrix algebra to address multidimensional problems. After a review of matrices, it delves into multiple regression, dependent random processes and autoregressive time series, spatial analysis using geostatistics and spatial regression, discriminant analysis, and a variety of multivariate analyses based on eigenvector methods. Build from Fundamental Concepts to Effective Problem Solving Each chapter starts with conceptual and theoretical material to give a firm foundation in how the methods work. Examples and exercises illustrate the applications and demonstrate how to go from concepts to problem solving. Hands-on computer sessions allow students to grasp the practical implications and learn by doing. Throughout, the computer examples and exercises use seeg and RcmdrPlugin.seeg, open-source R packages developed by the author, which help students acquire the skills to implement and conduct analysis and to analyze the results. This self-contained book offers a unified presentation of data analysis methods for more effective problem solving. With clear, easy-to-follow explanations, the book helps students to develop a solid understanding of basic statistical analysis and prepares them for learning the more advanced and specialized methods they will need in their work.

Einf Hrung In Statistik Und Messwertanalyse F R Physiker

Author: G. Bohm
Publisher:
ISBN: 9783540257592
Size: 71.26 MB
Format: PDF, Kindle
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Die Einf]hrung in die Statistik und Messwertanalyse f]r Physiker richtet sich weniger an mathematischen \berlegungen aus, sondern stellt die praktische Anwendung in den Vordergrund und schdrft die Intuition experimentelle Ergebnisse richtig einzuschdtzen. Zahlreiche ausf]hrlich betrachtete Beispiele dienen dazu, hdufig bei der Datenanalyse gemachte Fehler zu vermeiden (unsinnige Anwendung des Chi-Quadrattests, Funktionenanpassung bei falscher Parametrisierung, Entfaltung mit willk]rlicher Regularisierung). Ein besonderes Augenmerk wird auf den Vergleich von Daten mit Monte-Carlo-Simulationen gelenkt. Moderne Experimente kommen nicht ohne Simulation aus. Deshalb ist es wichtig zu wissen, wie Parameteranpassungen und Entfaltungen in diesem Fall durchgef]rt werden. Au_erdem werden den Studierenden moderne Entwicklungen der Statistik nahegebracht, die in dlteren Lehrb]chern nicht behandelt werden.