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Springer Modern Multidimensional Scaling - Statistics Book

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Description

Explore the complexities of data analysis with Modern Multidimensional Scaling: Theory and Applications from the Springer Series in Statistics. This text focuses on Multidimensional Scaling (MDS), a vital technique for analyzing similarity or dissimilarity data across various object sets. Whether you are working with intercorrelations of test items, political candidate similarity ratings, or international trade indices, MDS provides a way to model data as distances among points in a geometric space. By transforming complex arrays of numbers into a graphical display, this book helps you visualize the essential structure of your data. This method makes information much easier to understand while smoothing out noise to reveal true patterns. This Springer publication serves as a comprehensive resource for understanding the numerous varieties of MDS used in modern statistical analysis.

Key Features

This Springer Series in Statistics book covers the theory and applications of Multidimensional Scaling (MDS).

Learn to model similarity or dissimilarity data as distances among points in a geometric space.

Use MDS to transform complex arrays of numbers into clear graphical displays of data structures.

Apply these statistical techniques to diverse datasets including test item intercorrelations and trade indices.

Improve data interpretation by smoothing out noise to reveal the essential information within your data.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
04 August 2005
Listed Since
12 December 2006

Barcode

No barcode data available

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