Essays in Statistical Science PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Essays in Statistical Science PDF full book. Access full book title Essays in Statistical Science by Patrick Alfred Pierce Moran. Download full books in PDF and EPUB format.
Author: Patrick Alfred Pierce Moran
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 452
Get Book Here
Book Description
Genetics; Geometry and geometrical probability; Mathematical Human populations; Statistical theory; Stochastic processes; Time series.
Author: Patrick Alfred Pierce Moran
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 452
Get Book Here
Book Description
Genetics; Geometry and geometrical probability; Mathematical Human populations; Statistical theory; Stochastic processes; Time series.
Author: J. Gani
Publisher:
ISBN:
Category :
Languages : it
Pages : 434
Get Book Here
Book Description
Author: Joseph Mark Gani
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 434
Get Book Here
Book Description
Author: Joseph Mark Gani
Publisher:
ISBN:
Category :
Languages : en
Pages :
Get Book Here
Book Description
Author: C. M. Bray
Publisher:
ISBN: 9780582446403
Category : Mathematical statistics
Languages : en
Pages : 214
Get Book Here
Book Description
Author: Miles A. Kimball
Publisher: Routledge
ISBN: 135153761X
Category : Art
Languages : en
Pages : 330
Get Book Here
Book Description
Bringing together scholars from around the world, this collection examines many of the historical developments in making data visible through charts, graphs, thematic maps, and now interactive displays. Today, we are used to seeing data portrayed in a dizzying array of graphic forms. Virtually any quantified knowledge, from social and physical science to engineering and medicine, as well as business, government, or personal activity, has been visualized. Yet the methods of making data visible are relatively new innovations, most stemming from eighteenth- and nineteenth-century innovations that arose as a logical response to a growing desire to quantify everything-from science, economics, and industry to population, health, and crime. Innovators such as Playfair, Alexander von Humboldt, Heinrich Berghaus, John Snow, Florence Nightingale, Francis Galton, and Charles Minard began to develop graphical methods to make data and their relations more visible. In the twentieth century, data design became both increasingly specialized within new and existing disciplines-science, engineering, social science, and medicine-and at the same time became further democratized, with new forms that make statistical, business, and government data more accessible to the public. At the close of the twentieth century and the beginning of the twenty-first, an explosion in interactive digital data design has exponentially increased our access to data. The contributors analyze this fascinating history through a variety of critical approaches, including visual rhetoric, visual culture, genre theory, and fully contextualized historical scholarship.
Author: Dev Basu
Publisher: Springer
ISBN:
Category : Mathematics
Languages : en
Pages : 394
Get Book Here
Book Description
This book is a collection of essays on the foundations of Statistical Inference. The sequence in which the essays have been arranged makes it possible to read the book as a single contemporay discourse on the likelihood principle, the paradoxes that attend its violation, and the radical deviation from classical statistical practices that its adoption would entail. The book can also be read, with the aid of the notes as a chronicle of the development of Basu's ideas.
Author: Andriëtte Bekker
Publisher: Springer Nature
ISBN: 3030421961
Category : Medical
Languages : en
Pages : 543
Get Book Here
Book Description
In the statistical domain, certain topics have received considerable attention during the last decade or so, necessitated by the growth and evolution of data and theoretical challenges. This growth has invariably been accompanied by computational advancement, which has presented end users as well as researchers with the necessary opportunities to handle data and implement modelling solutions for statistical purposes. Showcasing the interplay among a variety of disciplines, this book offers pioneering theoretical and applied solutions to practice-oriented problems. As a carefully curated collection of prominent international thought leaders, it fosters collaboration between statisticians and biostatisticians and provides an array of thought processes and tools to its readers. The book thereby creates an understanding and appreciation of recent developments as well as an implementation of these contributions within the broader framework of both academia and industry. Computational and Methodological Statistics and Biostatistics is composed of three main themes: • Recent developments in theory and applications of statistical distributions;• Recent developments in supervised and unsupervised modelling;• Recent developments in biostatistics; and also features programming code and accompanying algorithms to enable readers to replicate and implement methodologies. Therefore, this monograph provides a concise point of reference for a variety of current trends and topics within the statistical domain. With interdisciplinary appeal, it will be useful to researchers, graduate students, and practitioners in statistics, biostatistics, clinical methodology, geology, data science, and actuarial science, amongst others.
Author: Miles A. Kimball
Publisher: Routledge
ISBN: 135153761X
Category : Art
Languages : en
Pages : 330
Get Book Here
Book Description
Bringing together scholars from around the world, this collection examines many of the historical developments in making data visible through charts, graphs, thematic maps, and now interactive displays. Today, we are used to seeing data portrayed in a dizzying array of graphic forms. Virtually any quantified knowledge, from social and physical science to engineering and medicine, as well as business, government, or personal activity, has been visualized. Yet the methods of making data visible are relatively new innovations, most stemming from eighteenth- and nineteenth-century innovations that arose as a logical response to a growing desire to quantify everything-from science, economics, and industry to population, health, and crime. Innovators such as Playfair, Alexander von Humboldt, Heinrich Berghaus, John Snow, Florence Nightingale, Francis Galton, and Charles Minard began to develop graphical methods to make data and their relations more visible. In the twentieth century, data design became both increasingly specialized within new and existing disciplines-science, engineering, social science, and medicine-and at the same time became further democratized, with new forms that make statistical, business, and government data more accessible to the public. At the close of the twentieth century and the beginning of the twenty-first, an explosion in interactive digital data design has exponentially increased our access to data. The contributors analyze this fascinating history through a variety of critical approaches, including visual rhetoric, visual culture, genre theory, and fully contextualized historical scholarship.
Author: M. S. Bartlett
Publisher: Springer Science & Business Media
ISBN: 9400958897
Category : Science
Languages : en
Pages : 156
Get Book Here
Book Description
Some years ago when I. assembled a number of general articles and lectures on probability and statistics, their publication (Essays in Probability and Statistics, Methuen, London, 1962) received a some what better reception than I had been led to expect of such a miscellany. I am consequently tempted to risk publishing this second collection, the title I have given it (taken from the first lecture) seeming to me to indicate a coherence in my articles which my publishers might otherwise be inclined to query. As in the first collection, the articles are reprinted chronologically, usually without comment. One exception is the third, not previously published and differing from the original spoken version both slightly where indicated in the text and by the addition of an Appendix. I apologize for the inevitable limitations due to date, and also for any occasional repetition of the discussion (e.g. on Bayesian methods in statistical inference). In particular, readers technically interested in the classification and use of nearest-neighbour models, a topic raised in Appendix II of the fourth article, should also refer to my monograph The Statistical Analysis of Spatial Pattern (Chapman and Hall, London, 1976), where a much more up-to-date account of these models will be found, and, incidentally, a further emphasis, if one is needed, of the common statistical theory of physics and biology. March 1975 M.S.B.
