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9780282496289: A Course in Geometry of N Dimensions (Classic Reprint)

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This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works. This text has been digitally restored from a historical edition. Some errors may persist, however we consider it worth publishing due to the work's historical value.
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Maurice G. Kendall
Edité par Forgotten Books, 2018
ISBN 10 : 0282496289 ISBN 13 : 9780282496289
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PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur LW-9780282496289

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Maurice G. Kendall
Edité par Forgotten Books, 2018
ISBN 10 : 0282496289 ISBN 13 : 9780282496289
Neuf PAP

Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni

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PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur LW-9780282496289

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Maurice G. Kendall
Edité par Forgotten Books, 2018
ISBN 10 : 0282496289 ISBN 13 : 9780282496289
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Paperback. Etat : New. Print on Demand. This book delves into the fascinating realm of n-dimensional geometry, a field that extends the familiar concepts of points, lines, and planes into higher-dimensional spaces. While the subject may seem abstract, the author skillfully demonstrates its practical applications, particularly in the field of statistics. Emerging from the work of mathematicians and physicists in the early 20th century, n-dimensional geometry provides a powerful tool for understanding complex statistical phenomena. The author guides readers through the fundamental principles of this geometry, including distance, angles, and volume in higher dimensions. The book explores various geometric figures in n dimensions, such as polytopes, simplexes, and hypercubes, and elucidates their properties. It delves into coordinate transformations, including the Helmert transformation, which has significant implications in statistical analysis. Central to the book's exploration is the concept of content, the n-dimensional analogue of volume. The author meticulously calculates the content of various geometric figures, including hyperspheres, hyperellipsoids, and hyperpyramids. These calculations provide a foundation for understanding probability distributions and statistical inference in higher dimensions. By bridging the gap between abstract geometric concepts and concrete statistical applications, this book offers valuable insights into the underlying structure of data and the methods used to analyze it. The author's clear explanations and illustrative examples make this complex subject accessible to students and researchers alike, ultimately revealing the profound connections between geometry and the world of data analysis. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. N° de réf. du vendeur 9780282496289_0

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