Spatial Analysis for the Social Sciences, Darmofal
Автор: Darmofal Название: Spatial Analysis for the Social Sciences ISBN: 0521716381 ISBN-13(EAN): 9780521716383 Издательство: Cambridge Academ Рейтинг: Цена: 4592.00 р. Наличие на складе: Поставка под заказ.
Описание: Spatial Analysis for the Social Sciences is for researchers across the social sciences who want to model and explain spatial interactions between the actors they study. The book is very user-friendly and demonstrates a variety of analytical approaches that applied researchers can use in their work.
Описание: Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. This work treats the basic and important topics in multivariate statistics.
Описание: Provides an introduction to the concepts of statistical analysis of data for students at undergraduate and graduate level. This text also provides tools for data reduction and error analysis commonly required in the physical sciences. It features a variety of numerical and graphical techniques, and emphasizes methods of handling data than theory.
Описание: Focuses on latent class analysis (LCA) and latent transition analysis (LTA) with a comprehensive treatment of longitudinal latent class models. This book includes examples that enable the reader to acquire a conceptual and technical understanding and to apply techniques to address empirical research questions.
Автор: Box-Steffensmeier Название: Time Series Analysis for the Social Sciences ISBN: 0521871166 ISBN-13(EAN): 9780521871167 Издательство: Cambridge Academ Рейтинг: Цена: 12355.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Time Series Analysis for the Social Sciences provides accessible, up-to-date instruction and examples of the core methods in time series econometrics. The book covers ARIMA models, time series regression, unit-root diagnosis, vector autoregressive models, error-correction models, intervention models, fractional integration, ARCH models, structural breaks, and forecasting.
Описание: Gregor Wiedemann evaluates text mining applications for social science studies with respect to conceptual integration of consciously selected methods, systematic optimization of algorithms and workflows, and methodological reflections relating to empirical research. In an exemplary study, he introduces workflows to analyze a corpus of around 600,000 newspaper articles on the subject of “democratic demarcation” in Germany. He provides a valuable resource for innovative measures to social scientists and computer scientists in the field of applied natural language processing.
Автор: Box-Steffensmeier Название: Time Series Analysis for the Social Sciences ISBN: 0521691559 ISBN-13(EAN): 9780521691550 Издательство: Cambridge Academ Рейтинг: Цена: 4592.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Time Series Analysis for the Social Sciences provides accessible, up-to-date instruction and examples of the core methods in time series econometrics. The book covers ARIMA models, time series regression, unit-root diagnosis, vector autoregressive models, error-correction models, intervention models, fractional integration, ARCH models, structural breaks, and forecasting.
Автор: Ruth Wodak; Michal Krzyzanowski Название: Qualitative Discourse Analysis in the Social Sciences ISBN: 0230019870 ISBN-13(EAN): 9780230019874 Издательство: Springer Рейтинг: Цена: 5868.00 р. Наличие на складе: Поставка под заказ.
Описание: What can language tell us about society? Looking at a range of genres, from political speeches to internet chat, this book shows how qualitative methods are used to analyse discourses throughout the social sciences. The practical problems of designing and conducting discourse-based research are solved in this key resource for all social scientists.
Описание: Suitable for students and researchers whose mathematical background is limited to basic algebra, this book focuses on fundamental elements of time series analysis that social scientists need to understand so they can employ time series analysis for their research and practice.
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