Advertisement
| statistical method in geography: Statistical Methods for Geographers W. A. V. Clark, P. L. Hosking, 1986-04-04 A textbook for advanced undergraduate/first year graduate level courses in statistical methods in geography. Presents methods useful in research design, hypothesis testing, and analyzing spatial and functional relationships. Introduces basic statistical terms and techniques for displaying and describing distributions, and covers a range of working methods including probability and sampling, simple linear regression, extensions of the simple linear model to multiple regression and its assumptions, stepwise logit regression, and canonical and discriminant analysis. |
| statistical method in geography: Statistics in Geography David Ebdon, 1977 |
| statistical method in geography: Statistical Methods for Climate Scientists Timothy DelSole, Michael Tippett, 2022-02-24 An accessible introduction to statistical methods for students in the climate sciences. |
| statistical method in geography: An Introduction to Statistical Problem Solving in Geography J. Chapman McGrew, Jr., Charles B. Monroe, 2009-04-22 Written for undergraduate geography majors and entry-level graduate students with limited backgrounds in statistical analysis and methods, McGrew and Monroe provide a comprehensive and understandable introduction to statistical methods in a problem-solving framework. Engaging examples and problems are drawn from a variety of topical areas in both human and physical geography and are fully integrated into the text. Without compromising statistical rigor or oversimplifying, the authors stress the importance of written narratives that explain each statistical technique. After introducing basic statistical concepts and terminology, the authors focus on nonspatial and spatial descriptive statistics. They transition to inferential problem solving, including probability, sampling, and estimation, before delving deeper into inferential statistics for geographic problem solving. The final chapters examine the related techniques of correlation and regression. A list of major goals and objectives is included at the end of each chapter, allowing students to monitor their own progress and mastery of geographic statistical materials. An epilogue, offering over 150 geographic situations, gives students a chance to figure out which statistical technique should be used for a particular situation. |
| statistical method in geography: Spatial Analysis Methods and Practice George Grekousis, 2020-06-11 An introductory overview of spatial analysis and statistics through GIS, including worked examples and critical analysis of results. |
| statistical method in geography: Statistical Methods for Geography Peter A Rogerson, 2010-02-11 The Third Edition of this bestselling student favorite has again been revised and updated to provide an expert introduction to the principal methods and techniques needed to understand a statistics module. Features new to this edition include: further introductory material; updated exercises and illustrative examples; updated downloadable datasets Statistical Methods is required reading for undergraduate modules in statistical analysis, statistical methods, and quantitative geography. |
| statistical method in geography: Quantitative Geography A Stewart Fotheringham, Chris Brunsdon, Martin Charlton, 2000-05-02 Integrating a discussion of the application of quantitative methods with practical examples, this book explains the philosophy of the new quantitative methodologies and contrasts them with the methods associated with geography's `Quantitative Revolution' of the 1960s. Key issues discussed include: the nature of modern quantitative geography; spatial data; geographical information systems; visualization; local analysis; point pattern analysis; spatial regression; and statistical inference. Concluding with a review of models used in spatial theory, the authors discuss the current challenges to spatial data analysis. Written to be accessible, to communicate the diversity and excitement of recent thinking, Quantitative Geog |
| statistical method in geography: Geodemographics, GIS and Neighbourhood Targeting Richard Harris, Peter Sleight, Richard Webber, 2005-12-13 Geodemographic classification is ‘big business’ in the marketing and service sector industries, and in public policy there has also been a resurgence of interest in neighbourhood initiatives and targeting. As an increasing number of professionals realise the potential of geographic analysis for their business or organisation, there exists a timely gap in the market for a focussed book on geodemographics and GIS. Geodemographics: neighbourhood targeting and GIS provides both an introduction to and overview of the methods, theory and classification techniques that provide the foundation of neighbourhood analysis and commercial geodemographic products. Particular focus is given to the presentation and use of neighbourhood classification in GIS. Authored by leading marketing professionals and a prominent academic, this book presents methods, theory and classification techniques in a reader-friendly manner Supported by private and public sector case studies and vignettes The applied ‘how to’ sections will specifically appeal to the intended audience at work in business and service planning Includes information on the recent UK and US Census products and resulting neighbourhood classifications |
| statistical method in geography: Statistical Geography Zamir Alvi, 2002 The use of statistical techniques in geography received an impetus only after the Second World War. Since then, application of statistical techniques in social sciences has increased enormously making it essential for geographers to acquire training in elementary statistical methods, particularly after the sixties when statistical geography came to occupy a distinct part of the post-graduate syllabus. The main object of this book is to introduce the students to some of the concepts of statistical analytical methods. The fundamentals of statistics have been elaborated so as to make it easily understandable even to those who do not have any background of mathematics. Greater emphasis has been laid on the application of statistical techniques in geography and hence each chapter has been punctuated with illustrations. The book especially deals with problems on standard deviation, probability, variance analysis, correlation, and regression which are indispensable for researchers in geography in general and in the social sciences in particular. |
| statistical method in geography: Spatial Statistics and Geostatistics Yongwan Chun, Daniel A Griffith, 2013-01-11 Ideal for anyone who wishes to gain a practical understanding of spatial statistics and geostatistics. Difficult concepts are well explained and supported by excellent examples in R code, allowing readers to see how each of the methods is implemented in practice - Professor Tao Cheng, University College London Focusing specifically on spatial statistics and including components for ArcGIS, R, SAS and WinBUGS, this book illustrates the use of basic spatial statistics and geostatistics, as well as the spatial filtering techniques used in all relevant programs and software. It explains and demonstrates techniques in: spatial sampling spatial autocorrelation local statistics spatial interpolation in two-dimensions advanced topics including Bayesian methods, Monte Carlo simulation, error and uncertainty. It is a systematic overview of the fundamental spatial statistical methods used by applied researchers in geography, environmental science, health and epidemiology, population and demography, and planning. A companion website includes digital R code for implementing the analyses in specific chapters and relevant data sets to run the R codes. |
| statistical method in geography: Research Methods in Geography Basil Gomez, John Paul Jones, III, 2010-05-10 This comprehensive textbook offers a conceptual and practical introduction to research methodology, data collection, and techniques used in both human and physical geography. Explores a full range of contemporary geographic techniques, including statistics, mathematical analysis, GIS, and remote sensing Unique in both content and organization, it brings together a team of internationally recognized specialists to create a balanced approach between physical geography, human geography, and research techniques Includes a series of foundational chapters offering multiple perspectives on the central questions in research methods Examines the conceptual frameworks and practical issues behind data acquisition and analysis, and how to interpret results Includes explanations of key terminology and exercises throughout |
| statistical method in geography: Learning Statistics Using R Randall E. Schumacker, 2014-02-03 Providing easy-to-use R script programs that teach descriptive statistics, graphing, and other statistical methods, Learning Statistics Using R shows readers how to run and utilize R, a free integrated statistical suite that has an extensive library of functions. Randall E. Schumacker’s comprehensive book describes in detail the processing of variables in statistical procedures. Covering a wide range of topics, from probability and sampling distribution to statistical theorems and chi-square, this introductory book helps readers learn not only how to use formulae to calculate statistics, but also how specific statistics fit into the overall research process. Learning Statistics Using R covers data input from vectors, arrays, matrices and data frames, as well as the input of data sets from SPSS, SAS, STATA and other software packages. Schumacker’s text provides the freedom to effectively calculate, manipulate, and graphically display data, using R, on different computer operating systems without the expense of commercial software. Learning Statistics Using R places statistics within the framework of conducting research, where statistical research hypotheses can be directly addressed. Each chapter includes discussion and explanations, tables and graphs, and R functions and outputs to enrich readers′ understanding of statistics through statistical computing and modeling. |
| statistical method in geography: Statistical Analysis Quick Reference Guidebook Alan C. Elliott, Wayne A. Woodward, 2007 A practical `cut to the chase′ handbook that quickly explains the when, where, and how of statistical data analysis as it is used for real-world decision-making in a wide variety of disciplines. In this one-stop reference, the authors provide succinct guidelines for performing an analysis, avoiding pitfalls, interpreting results and reporting outcomes. |
| statistical method in geography: Statistical Methods and the Geographer Stanley Gregory, 2014-09-25 First published in 1978. For the non-mathematician, however, even the simpler introductory books on statistics often raise considerable problems. In this second edition First, some attention has been given to the problem of the transformation of data in order to reinforce the appreciation of the need for normally-distributed data for the use of so many techniques. Secondly, the use of probability paper, at least in simple terms, has been introduced to illustrate the ways in which the labour of probability assessments can be circumvented. Thirdly, radical changes have been made, plus considerable expansion added, to the theme of non-parametric testing, to provide a more systematic approach to what is a most important group of possible techniques for geographers. Fourthly, change and expansion are also reflected in the sections on correlation and regression, including some simple consideration of curvilinear relationships and the presentation of computational techniques more geared to the use of desk calculators rather than long-hand methods. Finally, the bibliography has also been expanded, to incorporate a wider range of books on techniques and a selection of research papers using such techniques in a geographical (or near-geographical) context. |
| statistical method in geography: Statistical Analysis of Circular Data N. I. Fisher, 1995-10-12 A unified, up-to-date account of circular data-handling techniques, useful throughout science. |
| statistical method in geography: An Introduction to Scientific Research Methods in Geography and Environmental Studies Daniel Montello, Paul Sutton, 2012-12-10 Covers a broad range of subjects that undergraduates in the discipline should be familiar and comfortable with upon graduation. From chapters on the scientific method and fundamental research concepts, to experimental design, sampling and statistical analysis, the text offers an excellent introduction to the key concepts of geographical research. The content is applicable for students at the beginning of their studies right through to planning and conducting dissertations. The book has also been of particular support in designing my level 1 and 2 tutorials which cover similar ground to several of the chapters. - Joseph Mallalieu, School of Geography, Leeds University Montello and Sutton is one of the best texts I′ve used in seminars on research methodology. The text offers a clear balance of quantitative vs. qualitative and physical vs. human which I′ve found particularly valuable. The chapters on research ethics, scientific communication, information technologies and data visualization are excellent. - Kenneth E. Foote, Department of Geography, University of Colorado at Boulder This is a broad and integrative introduction to the conduct and interpretation of scientific research, covering both geography and environmental studies. Written for undergraduate and postgraduate students, it: Explains both the conceptual and the technical aspects of research, as well as all phases of the research process Combines approaches in physical geography and environmental science, human geography and human-environment relations, and geographic and environmental information techniques (such as GIS, cartography, and remote sensing) Combines natural and social scientific approaches common to subjects in geography and environmental studies Includes case studies of actual research projects to demonstrate the breadth of approaches taken It will be core reading for students studying scientific research methods in geography, environmental studies and related disciplines such as planning and earth science. |
| statistical method in geography: Statistics for Geography and Environmental Science Richard Harris, Claire Jarvis, 2014-05-01 Statistics are important tools for validating theory, making predictions and engaging in policy research. They help to provide informed commentary about social and environmental issues, and to make the case for change. Knowledge of statistics is therefore a necessary skill for any student of geography or environmental science. This textbook is aimed at students on a degree course taking a module in statistics for the first time. It focuses on analysing, exploring and making sense of data in areas of core interest to physical and human geographers, and to environmental scientists. It covers the subject in a broadly conventional way from descriptive statistics, through inferential statistics to relational statistics but does so with an emphasis on applied data analysis throughout. |
| statistical method in geography: Statistical Methods for Environmental Pollution Monitoring Richard O. Gilbert, 1987-02-15 This book discusses a broad range of statistical design and analysis methods that are particularly well suited to pollution data. It explains key statistical techniques in easy-to-comprehend terms and uses practical examples, exercises, and case studies to illustrate procedures. Dr. Gilbert begins by discussing a space-time framework for sampling pollutants. He then shows how to use statistical sample survey methods to estimate average and total amounts of pollutants in the environment, and how to determine the number of field samples and measurements to collect for this purpose. Then a broad range of statistical analysis methods are described and illustrated. These include: * determining the number of samples needed to find hot spots * analyzing pollution data that are lognormally distributed * testing for trends over time or space * estimating the magnitude of trends * comparing pollution data from two or more populations New areas discussed in this sourcebook include statistical techniques for data that are correlated, reported as less than the measurement detection limit, or obtained from field-composited samples. Nonparametric statistical analysis methods are emphasized since parametric procedures are often not appropriate for pollution data. This book also provides an illustrated comprehensive computer code for nonparametric trend detection and estimation analyses as well as nineteen statistical tables to permit easy application of the discussed statistical techniques. In addition, many publications are cited that deal with the design of pollution studies and the statistical analysis of pollution data. This sourcebook will be a useful tool for applied statisticians, ecologists, radioecologists, hydrologists, biologists, environmental engineers, and other professionals who deal with the collection, analysis, and interpretation of pollution in air, water, and soil. |
| statistical method in geography: Federal Statistics, Multiple Data Sources, and Privacy Protection National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Committee on National Statistics, Panel on Improving Federal Statistics for Policy and Social Science Research Using Multiple Data Sources and State-of-the-Art Estimation Methods, 2018-01-27 The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics. The panel's first report described federal statistical agencies' current paradigm, which relies heavily on sample surveys for producing national statistics, and challenges agencies are facing; the legal frameworks and mechanisms for protecting the privacy and confidentiality of statistical data and for providing researchers access to data, and challenges to those frameworks and mechanisms; and statistical agencies access to alternative sources of data. The panel recommended a new approach for federal statistical programs that would combine diverse data sources from government and private sector sources and the creation of a new entity that would provide the foundational elements needed for this new approach, including legal authority to access data and protect privacy. This second of the panel's two reports builds on the analysis, conclusions, and recommendations in the first one. This report assesses alternative methods for implementing a new approach that would combine diverse data sources from government and private sector sources, including describing statistical models for combining data from multiple sources; examining statistical and computer science approaches that foster privacy protections; evaluating frameworks for assessing the quality and utility of alternative data sources; and various models for implementing the recommended new entity. Together, the two reports offer ideas and recommendations to help federal statistical agencies examine and evaluate data from alternative sources and then combine them as appropriate to provide the country with more timely, actionable, and useful information for policy makers, businesses, and individuals. |
| statistical method in geography: Statistical Methods Of Analysis Chin Long Chiang, 2003-10-01 This textbook systematically presents fundamental methods of statistical analysis: from probability and statistical distributions, through basic concepts of statistical inference, to a collection of methods of analysis useful for scientific research. It is rich in tables, diagrams, and examples, in addition to theoretical justification of the methods of analysis introduced. Each chapter has a section entitled “Exercises and Problems” to accompany the text. There are altogether about 300 exercises and problems, answers to the selected problems are given. A section entitled “Proof of the Results in This Chapter” in each chapter provides interested readers with material for further study. |
| statistical method in geography: Creative Methods for Human Geographers Nadia von Benzon, Mark Holton, Catherine Wilkinson, Samantha Wilkinson, 2021-01-13 Introducing a broad range of innovative and creative qualitative methods, this accessible book shows you how to use them in research project while providing straightforward advice on how to approach every step of the process, from planning and organisation to writing up and disseminating research. It offers: Demonstration of creative methods using both primary or secondary data. Practical guidance on overcoming common hurdles, such as getting ethical clearance and conducting a risk assessment. Encouragement to reflect critically on the processes involved in research. The authors provide a complete toolkit for conducting research in geography, while ensuring the most cutting-edge methods are unintimidating to the reader. |
| statistical method in geography: Practical Statistics David Kremelberg, 2010-03-18 Making statistics—and statistical software—accessible and rewarding This book provides readers with step-by-step guidance on running a wide variety of statistical analyses in IBM® SPSS® Statistics, Stata, and other programs. Author David Kremelberg begins his user-friendly text by covering charts and graphs through regression, time-series analysis, and factor analysis. He provides a background of the method, then explains how to run these tests in IBM SPSS and Stata. He then progresses to more advanced kinds of statistics such as HLM and SEM, where he describes the tests and explains how to run these tests in their appropriate software including HLM and AMOS. This is an invaluable guide for upper-level undergraduate and graduate students across the social and behavioral sciences who need assistance in understanding the various statistical packages. |
| statistical method in geography: Geographically Weighted Regression A. Stewart Fotheringham, Chris Brunsdon, Martin Charlton, 2003-02-21 Geographical Weighted Regression (GWR) is a new local modelling technique for analysing spatial analysis. This technique allows local as opposed to global models of relationships to be measured and mapped. This is the first and only book on this technique, offering comprehensive coverage on this new 'hot' topic in spatial analysis. * Provides step-by-step examples of how to use the GWR model using data sets and examples on issues such as house price determinants, educational attainment levels and school performance statistics * Contains a broad discussion of and basic concepts on GWR through to ideas on statistical inference for GWR models * uniquely features accompanying author-written software that allows users to undertake sophisticated and complex forms of GWR within a user-friendly, Windows-based, front-end (see book for details). |
| statistical method in geography: Key Methods in Geography Nicholas Clifford, Gill Valentine, 2010-05-30 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. |
| statistical method in geography: Your Statistical Consultant Rae R. Newton, Kjell Erik Rudestam, 2013 How do you bridge the gap between what you learned in your statistics course and the questions you want to answer in your real-world research? Oriented towards distinct questions in a How do I? or When should I? format, Your Statistical Consultant is the equivalent of the expert colleague down the hall who fields questions about describing, explaining, and making recommendations regarding thorny or confusing statistical issues. The book serves as a compendium of statistical knowledge, both theoretical and applied, that addresses the questions most frequently asked by students, researchers and instructors. Written to be responsive to a wide range of inquiries and levels of expertise, the book is flexibly organized so readers can either read it sequentially or turn directly to the sections that correspond to their concerns. |
| statistical method in geography: Spatial Analysis of Coastal Environments Sarah M. Hamylton, 2017-04-13 This book covers the spatial analytical tools needed to map, monitor and explain or predict coastal features, with accompanying online exercises. |
| statistical method in geography: Modern Statistical Methods for Astronomy Eric D. Feigelson, G. Jogesh Babu, 2012-07-12 Modern astronomical research is beset with a vast range of statistical challenges, ranging from reducing data from megadatasets to characterizing an amazing variety of variable celestial objects or testing astrophysical theory. Linking astronomy to the world of modern statistics, this volume is a unique resource, introducing astronomers to advanced statistics through ready-to-use code in the public domain R statistical software environment. The book presents fundamental results of probability theory and statistical inference, before exploring several fields of applied statistics, such as data smoothing, regression, multivariate analysis and classification, treatment of nondetections, time series analysis, and spatial point processes. It applies the methods discussed to contemporary astronomical research datasets using the R statistical software, making it invaluable for graduate students and researchers facing complex data analysis tasks. A link to the author's website for this book can be found at www.cambridge.org/msma. Material available on their website includes datasets, R code and errata. |
| statistical method in geography: Spatial Data Analysis Robert P. Haining, 2003-04-17 Spatial Data Analysis: Theory and Practice, first published in 2003, provides a broad ranging treatment of the field of spatial data analysis. It begins with an overview of spatial data analysis and the importance of location (place, context and space) in scientific and policy related research. Covering fundamental problems concerning how attributes in geographical space are represented to the latest methods of exploratory spatial data analysis and spatial modeling, it is designed to take the reader through the key areas that underpin the analysis of spatial data, providing a platform from which to view and critically appreciate many of the key areas of the field. Parts of the text are accessible to undergraduate and master's level students, but it also contains sufficient challenging material that it will be of interest to geographers, social and economic scientists, environmental scientists and statisticians, whose research takes them into the area of spatial analysis. |
| statistical method in geography: Point Pattern Analysis Barry N. Boots, Arthur Getis, 1988-03 Boots and Getis provide a concise explanation of point pattern analysis - a series of techniques for identifying patterns of clustering or regularity in a set of geographical locations. They discuss quadrat and distance methods of measurement, and consider the problems associated with these methods. The authors also outline and compare other measures of arrangement, suggesting when these techniques should be used. |
| statistical method in geography: How to Manage, Analyze, and Interpret Survey Data Arlene Fink, 2003 Shows how to manage survey data and become better users of statistical and qualitative survey information. This book explains the basic vocabulary of data management and statistics, and demonstrates the principles and logic behind the selection and interpretation of commonly used statistical and qualitative methods to analyze survey data. |
| statistical method in geography: Statistical Methods for Geography Peter A Rogerson, 2014-11-11 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 method in geography: Practical Statistics for Students Louis Cohen, Michael Holliday, 1996-09-28 This bestselling textbook is designed to help students understand parametric and nonparametric statistical methods so that they can tackle research problems successfully. By working through this book carefully and systematically, those who may not have a strong background in mathematics will gain a thorough grasp of the most widely used statistical methods in the social sciences. |
| statistical method in geography: Spatial Statistics and Models G.L. Gaile, C. Willmott, 2013-11-27 The quantitative revolution in geography has passed. The spirited debates of the past decades have, in one sense, been resolved by the inclusion of quantitative techniques into the typical geographer's set of methodological tools. A new decade is upon us. Throughout the quantitative revolution, geographers ransacked related disciplines and mathematics in order to find tools which might be applicable to problems of a spatial nature. The early success of Berry and Marble's Spatial Analysis and Garrison and Marble's volumes on Quantitative Geog raphy is testimony to their accomplished search. New developments often depend heavily on borrowed ideas. It is only after these developments have been established that the necessary groundwork for true innovation ob tains. In the last decade, geographers significantly -augmented their methodologi cal base by developing quantitative techniques which are specifically directed towards analysis of explicitly spatial problems. It should be pointed out, however, that the explicit incorporation of space into quantitative techniques has not been the sole domain of geographers. Mathematicians, geologists, meteorologists, economists, and regional scientists have shared the geo grapher's interest in the spatial component of their analytical tools. |
| statistical method in geography: Scope and Methods of Geography Halford John Mackinder, 2020-02 Is geography one, or is it several subjects? More precisely, are physical and political geography two stages of one investigation, or are they separate subjects to be studied by different methods, the one an appendix of geology, the other of history? --Halford Mackinder in The Scope and Methods of Geography, 1887 The Scope and Methods of Geography was published by Halford Mackinder in 1887 in the New Monthly Series of the Royal Geographical Society. It was a manifesto for the New Geography, in which he viewed physical geography and human geography as a single discipline. This publication represented the beginning of an illustrious career as an English geographer and academic. |
| statistical method in geography: Statistical Power Analysis for the Behavioral Sciences Jacob Cohen, 2013-05-13 Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of qualifying dependent variables and; * expanded power and sample size tables for multiple regression/correlation. |
| statistical method in geography: Statistical Data Analysis Glen Cowan, 1998-03-26 This book is a guide to the practical application of statistics in data analysis as typically encountered in the physical sciences. It is primarily addressed at students and professionals who need to draw quantitative conclusions from experimental data. Although most of the examples are taken from particle physics, the material is presented in a sufficiently general way as to be useful to people from most branches of the physical sciences. The first part of the book describes the basic tools of data analysis: concepts of probability and random variables, Monte Carlo techniques, statistical tests, and methods of parameter estimation. The last three chapters are somewhat more specialized than those preceding, covering interval estimation, characteristic functions, and the problem of correcting distributions for the effects of measurement errors (unfolding). |
| statistical method in geography: 100 Statistical Tests Gopal K Kanji, 2006-07-18 ′This is a very valuable book for statisticians and users of statistics. It contains a remarkable number of statistical tests which are currently available and useful for practical purposes′ - Statistical Papers This expanded and updated Third Edition of Gopal Kanji′s best-selling resource on statistical tests covers all the most commonly used tests with information on how to calculate and interpret results with simple datasets. Each entry begins with a short summary statement about the test′s purpose, and contains details of the test objective, the limitations (or assumptions) involved, a brief outline of the method, a worked example and the numerical calculation. This new edition also includes: A brand new introduction to statistical testing with information to guide the reader through the book so that even non-statistics students can find information quickly and easily Real-world explanations of how and when to use each test with examples drawn from wide range of disciplines. A useful Classification of Tests table All the relevant statistical tables for checking critical values 100 Statistical Tests: Third Edition is the one indispensable guide for users of statistical materials and consumers of statistical information at all levels and across all disciplines. |
| statistical method in geography: An Introduction to Scientific Research Methods in Geography Daniel Montello, Paul Sutton, 2006-03-06 This text provides a broad and integrative introduction to the conduct and interpretation of scientific research in geography. It covers both conceptual and technical aspects, and is applicable to all topical areas in geographic research, including human and physical geography, and geographic information science. The text discusses all parts of the research process, including scientific philosophy; basic research concepts; generating research ideas; communicating research and using library resources; sampling and research design; quantitative and qualitative data collection; data analysis, display, and interpretation; reliability and validity; using geographic information techniques in research; and ethical conduct in research. |
| statistical method in geography: Statistical Rethinking Richard McElreath, 2016-01-05 Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas. |
| statistical method in geography: Spationomy Vít Pászto, Carsten Jürgens, Polona Tominc, Jaroslav Burian, 2019-11-06 This open access book is based on Spationomy – Spatial Exploration of Economic Data, an interdisciplinary and international project in the frame of ERASMUS+ funded by the European Union. The project aims to exchange interdisciplinary knowledge in the fields of economics and geomatics. For the newly introduced courses, interdisciplinary learning materials have been developed by a team of lecturers from four different universities in three countries. In a first study block, students were taught methods from the two main research fields. Afterwards, the knowledge gained had to be applied in a project. For this international project, teams were formed, consisting of one student from each university participating in the project. The achieved results were presented in a summer school a few months later. At this event, more methodological knowledge was imparted to prepare students for a final simulation game about spatial and economic decision making. In a broader sense, the chapters will present the methodological background of the project, give case studies and show how visualisation and the simulation game works. |
STATISTICAL Definition & Meaning - Merriam-Webster
The meaning of STATISTICAL is of, relating to, based on, or employing the principles of statistics. How to use statistical in a sentence.
STATISTICAL | English meaning - Cambridge Dictionary
There is very little statistical evidence. It was designed to facilitate the combination of qualitative methods with statistical analysis. The generalizations are advanced on the basis of statistical …
Statistics - Wikipedia
Statistics is the discipline that deals with data, facts and figures with which meaningful information is inferred. Data may represent a numerical value, in form of quantitative data, or a label, as …
STATISTICAL Definition & Meaning | Dictionary.com
of, pertaining to, consisting of, or based on statistics. statistics. Examples have not been reviewed. In doing so, the judges said she could not point to “background circumstances” or …
What is Statistical Analysis? - GeeksforGeeks
Apr 15, 2025 · Statistical Analysis means gathering, understanding, and showing data to find patterns and connections that can help us make decisions. It includes lots of different ways to …
Statistics | Definition, Types, & Importance | Britannica
May 20, 2025 · statistics, the science of collecting, analyzing, presenting, and interpreting data. Governmental needs for census data as well as information about a variety of economic …
Statistical - definition of statistical by The Free Dictionary
Define statistical. statistical synonyms, statistical pronunciation, statistical translation, English dictionary definition of statistical. adj. Of, relating to, or employing statistics or the principles of …
STATISTICAL definition and meaning | Collins English Dictionary
Statistical means relating to the use of statistics. The report contains a great deal of statistical information. Of or relating to statistics.... Click for English pronunciations, examples sentences, …
Introduction to Research Statistical Analysis: An Overview of the ...
This article covers many statistical ideas essential to research statistical analysis. Sample size is explained through the concepts of statistical significance level and power.
Statistics - Definition, Examples, Mathematical Statistics
Statistics is defined as the process of collection of data, classifying data, representing the data for easy interpretation, and further analysis of data. Statistics also is referred to as arriving at …
STATISTICAL Definition & Meaning - Merriam-Webster
The meaning of STATISTICAL is of, relating to, based on, or employing the principles of statistics. How to use statistical in a …
STATISTICAL | English meaning - Cambridge Dictionary
There is very little statistical evidence. It was designed to facilitate the combination of qualitative methods with statistical …
Statistics - Wikipedia
Statistics is the discipline that deals with data, facts and figures with which meaningful information is inferred. Data may represent a numerical value, in form of quantitative …
STATISTICAL Definition & Meaning | Dictionary.com
of, pertaining to, consisting of, or based on statistics. statistics. Examples have not been reviewed. In doing so, the judges said she could not point to “background …
What is Statistical Analysis? - GeeksforGeeks
Apr 15, 2025 · Statistical Analysis means gathering, understanding, and showing data to find patterns and connections that can help us make decisions. It includes lots of …
