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The chapter examines the role of geospatial data in Russia's online ecosystem. Facilitated by the rise of geographic information systems and user-generated content, the distribution of geospatial data has blurred the line between physical spaces and their virtual representations. The chapter discusses different sources of these data available for Digital Russian Studies (e.g., social data and crowdsourced databases) together with the novel techniques for extracting geolocation from various data formats (e.g., textual documents and images). It also scrutinizes different ways of using these data, varying from mapping the spatial distribution of social and political phenomena to investigating the use of geotag data for cultural practices' digitization to exploring the use of geoweb for narrating individual and collective identities online.

Cover -- Title Page -- Copyright Page -- Dedication -- Acknowledgments -- Preface -- Table of Contents -- 1: RANDOM PROCESSES -- STOCHASTIC PROCESSES IN THE ENVIRONMENT -- STRUCTURE OF BOOK -- 2: THEORY OF PROBABILITY -- PROBABILITY CONCEPTS -- PROBABILITY LAWS -- CONDITIONAL PROBABILITY AND BAYES' THEOREM -- Bayes' Theorem -- SUMMARY -- PROBLEMS -- 3: PROBABILITY MODELS -- DISCRETE PROBABILITY MODELS -- Geometric Distribution -- CONTINUOUS RANDOM VARIABLES -- Uniform Distribution -- Computer Simulation -- Exponential Distribution -- MOMENTS, EXPECTED VALUE, AND CENTRAL TENDENCY -- VARIANCE, KURTOSIS, AND SKEWNESS -- ANALYSIS OF OBSERVED DATA -- Computing Statistics from Data -- Histograms and Frequency Plots -- Fitting Probability Models to Environmental Data -- Tail Exponential Method -- SUMMARY -- PROBLEMS -- 4: BERNOULLI PROCESSES -- CONDITIONS FOR BERNOULLI PROCESS -- DEVELOPMENT OF MODEL -- Example: Number of Persons Engaged in Cigarette Smoking -- Development of Model by Inductive Reasoning -- BINOMIAL DISTRIBUTION -- APPLICATIONS TO ENVIRONMENTAL PROBLEMS -- Probability Distribution for the Number of Exceedances -- Robustness of Statistical Assumptions -- COMPUTATION OF B(n,p) -- PROBLEMS -- 5: POISSON PROCESSES -- CONDITIONS FOR POISSON PROCESS -- DEVELOPMENT OF MODEL -- POISSON DISTRIBUTION -- EXAMPLES -- APPLICATIONS TO ENVIRONMENTAL PROBLEMS -- Probability Distribution for the Number of Exceedances -- COMPUTATION OF P(λt) -- PROBLEMS -- 6: DIFFUSION AND DISPERSION OF POLLUTANTS WEDGE MACHINE -- WEDGE MACHINE -- Distribution with Respect to Space -- Distribution with Respect to Time -- Summary and Discussion -- PARTICLE FRAME MACHINE -- PLUME MODEL -- SUMMARY AND CONCLUSIONS -- PROBLEMS -- 7: NORMAL PROCESSES -- CONDITIONS FOR NORMAL PROCESS -- DEVELOPMENT OF MODEL -- Summing Processes -- Averaging Processes -- CONFIDENCE INTERVALS

This accessible introduction to the theory and practice of longitudinal research takes the reader through the strengths and weaknesses of this kind of research, making clear: how to design a longitudinal study; how to collect data most effectively; how to make the best use of statistical techniques; and how to interpret results. Although the book provides a broad overview of the field, the focus is always on the practical issues arising out of longitudinal research. This book supplies the student with all that they need to get started and acts as a manual for dealing with opportunities and pitfalls. It is the ideal primer for this growing area of social research.

Lisp-Stat is a statistical computing environment based on the Lisp language. To support statistical computations, standard Lisp functions have been modified to operate in a vectorized fashion on lists and arrays of numbers, and a number of basic statistical functions have been added. Interactive graphical displays such as histograms, scatterplots, and rotatable three-dimensional scatterplots can be linked to show corresponding points in different plots. The graphics are implemented using an object-oriented programming system that is designed to support user-level extensions and customization. This article provides a brief introduction to the Lisp-Stat system, illustrating some of its capabilities in the context of the Duncan occupational status data.

A specter is haunting political science. It is the specter of methodological perfectionism. This dogma places methods before substance and imposes a narrow spectrum of accept-able methods on the discipline

This book takes both a retrospective and prospective view of the field of spatial analysis by combining selected reprints of classic articles by Arthur Getis with current observations by leading experts in the field. Four main aspects are highlighted, dealing with spatial analysis, pattern analysis, local statistics as well as illustrative empirical applications. Researchers and students will gain an appreciation of Getis' methodological contributions to spatial analysis and the broad impact of the methods he has helped pioneer on an impressively broad array of disciplines including spatial epidemiology, demography, economics, and ecology. The volume is a compilation of high impact original contributions, as evidenced by citations, and the latest thinking on the field by leading scholars. This makes the book ideal for advanced seminars and courses in spatial analysis as well as a key resource for researchers seeking a comprehensive overview of recent advances and future directions in the field.