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Before he became a professional architect, Christopher Wren had a highly successful career as an astronomer - he was Savilian Professor of Astronomy at Oxford University - and he was actively involved in many branches of the science or 'natural philosophy' of his day. This side of his career has, until now, been neglected by historians and biographers, and has been regarded as distinct and separate. This book contains the first detailed account of Wren's natural philosophy and, in addition, after showing that 'science' and 'architecture' were not then distinct in the way we understand them today, it presents a new perspective on Wren's architectural philosophy. The book will be of value to anyone interested in the history of science or of architecture.

Book is in very good condition and may include minimal underlining highlighting. The book can also include "From the library of" labels. May not contain miscellaneous items toys, dvds, etc. . We offer 100% money back guarantee and 24 7 customer service.

Before he became a professional architect, Christopher Wren had a highly successful career as an astronomer - he was Savilian Professor of Astronomy at Oxford University - and he was actively involved in many branches of the science or 'natural philosophy' of his day. This side of his career has, until now, been neglected by historians and biographers, and has been regarded as distinct and separate. This book contains the first detailed account of Wren's natural philosophy and, in addition, after showing that 'science' and 'architecture' were not then distinct in the way we understand them today, it presents a new perspective on Wren's architectural philosophy. The book will be of value to anyone interested in the history of science or of architecture.

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This comprehensive dictionary provides clear, concise definitions of terms from chemistry, physics, the geological sciences, and astronomy. The breadth of coverage and the accuracy of the entries are unsurpassed. Symbols and abbreviations are spelled out, and any unfamiliar terms used in making the definitions are themselves defined in the dictionary. The author has included quantitative information wherever pertinent, and has added a number of tables in the appendix to provide additional data. The most comprehensive dictionary available in the physical sciences, this readable, convenient reference will be essential for students and researchers in earth sciences, physics, chemistry and astronomy, as well as for educated lay readers with an interest in science.

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Data-Driven Seo with Python: Solve Seo Challenges with Data Science Using Python 2.29

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This is the second edition of Wil van der Aalst’s seminal book on process mining, which now discusses the field also in the broader context of data science and big data approaches. It includes several additions and updates, e.g. on inductive mining techniques, the notion of alignments, a considerably expanded section on software tools and a completely new chapter of process mining in the large. It is self-contained, while at the same time covering the entire process-mining spectrum from process discovery to predictive analytics. After a general introduction to data science and process mining in Part I, Part II provides the basics of business process modeling and data mining necessary to understand the remainder of the book. Next, Part III focuses on process discovery as the most important process mining task, while Part IV moves beyond discovering the control flow of processes, highlighting conformance checking, and organizational and time perspectives. Part V offers a guide to successfully applying process mining in practice, including an introduction to the widely used open-source tool ProM and several commercial products. Lastly, Part VI takes a step back, reflecting on the material presented and the key open challenges.  Overall, this book provides a comprehensive overview of the state of the art in process mining. It is intended for business process analysts, business consultants, process managers, graduate students, and BPM researchers.

Qualitative and Mixed Methods Data Analysis Using Dedoose®: A Practical Approach for Research Across the Social Sciences by Michelle Salmona, Eli Lieber, Dan Kaczynski provides both new and experienced researchers with a guided introduction to dealing with the methodological complexity of mixed methods and qualitative inquiry using Dedoose® software. The authors use their depth of experience designing and updating Dedoose® as well as their published research to give the reader practical strategies for using Dedoose® from a wide range of research studies. Case study contributions by outside researchers provide readers with rich examples of how to use Dedoose® in practical, applied social science and health settings.

Acceptable/Fair condition. Book is worn, but the pages are complete, and the text is legible. Has wear to binding and pages, may be ex-library. 0.71

Highly recommended by the Journal of Official Statistics, The American Statistician, and other journals, Applied Survey Data Analysis, Second Edition provides an up-to-date overview of state-of-the-art approaches to the analysis of complex sample survey data. Building on the wealth of material on practical approaches to descriptive analysis and regression modeling from the first edition, this second edition expands the topics covered and presents more step-by-step examples of modern approaches to the analysis of survey data using the newest statistical software. Designed for readers working in a wide array of disciplines who use survey data in their work, this book continues to provide a useful framework for integrating more in-depth studies of the theory and methods of survey data analysis. An example-driven guide to the applied statistical analysis and interpretation of survey data, the second edition contains many new examples and practical exercises based on recent versions of real-world survey data sets. Although the authors continue to use Stata for most examples in the text, they also continue to offer SAS, SPSS, SUDAAN, R, WesVar, IVEware, and Mplus software code for replicating the examples on the book’s updated website.

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Understanding spatial statistics requires tools from applied and mathematical statistics, linear model theory, regression, time series, and stochastic processes. It also requires a mindset that focuses on the unique characteristics of spatial data and the development of specialized analytical tools designed explicitly for spatial data analysis. Statistical Methods for Spatial Data Analysis answers the demand for a text that incorporates all of these factors by presenting a balanced exposition that explores both the theoretical foundations of the field of spatial statistics as well as practical methods for the analysis of spatial data. This book is a comprehensive and illustrative treatment of basic statistical theory and methods for spatial data analysis, employing a model-based and frequentist approach that emphasizes the spatial domain. It introduces essential tools and approaches including: measures of autocorrelation and their role in data analysis; the background and theoretical framework supporting random fields; the analysis of mapped spatial point patterns; estimation and modeling of the covariance function and semivariogram; a comprehensive treatment of spatial analysis in the spectral domain; and spatial prediction and kriging. The volume also delivers a thorough analysis of spatial regression, providing a detailed development of linear models with uncorrelated errors, linear models with spatially-correlated errors and generalized linear mixed models for spatial data. It succinctly discusses Bayesian hierarchical models and concludes with reviews on simulating random fields, non-stationary covariance, and spatio-temporal processes.Additional material on the CRC Press website supplements the content of this book. The site provides data sets used as examples in the text, software code that can be used to implement many of the principal methods described and illustrated, and updates to the text itself.

Fulfilling the need for a practical user’s guide, Statistics in MATLAB: A Primer provides an accessible introduction to the latest version of MATLAB® and its extensive functionality for statistics. Assuming a basic knowledge of statistics and probability as well as a fundamental understanding of linear algebra concepts, this book: Covers capabilities in the main MATLAB package, the Statistics Toolbox, and the student version of MATLAB Presents examples of how MATLAB can be used to analyze data Offers access to a companion website with data sets and additional examples Contains figures and visual aids to assist in application of the software Explains how to determine what method should be used for analysis Statistics in MATLAB: A Primer is an ideal reference for undergraduate and graduate students in engineering, mathematics, statistics, economics, biostatistics, and computer science. It is also appropriate for a diverse professional market, making it a valuable addition to the libraries of researchers in statistics, computer science, data mining, machine learning, image analysis, signal processing, and engineering.

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Book is in Used-VeryGood condition. Pages and cover are clean and intact. Used items may not include supplementary materials such as CDs or access codes. May show signs of minor shelf wear and contain very limited notes and highlighting. 2.07

Good condition. This is the average used book, that has all pages or leaves present, but may include writing. Book may be ex-library with stamps and stickers. 0.9