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Springer Matrix-Based Introduction to Multivariate Data Analysis - Springer

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Description

This textbook makes multivariate data analysis accessible to readers without matrix expertise by explaining procedures through matrix forms and revealing the underlying models and objective functions. Structured for intuitive understanding, it presents numerical examples before mathematical descriptions, enabling rapid comprehension of how multivariate analysis procedures work. The book clarifies the purposes and applications of various techniques in social sciences, medical research, and data analysis, making it an ideal resource for students and professionals seeking to master multivariate methods without extensive mathematical prerequisites.

Key Features

Matrix-based approach enables readers unfamiliar with matrices to grasp multivariate analysis procedures clearly and systematically.

Numerical examples precede mathematical descriptions throughout the textbook, building intuitive understanding before formal theory.

Explains underlying models and objective functions for each procedure, helping readers understand why specific methods are used.

Organized for practical application in biography, medical, legal and social sciences research contexts.

Springer publication ensures rigorous academic standards and comprehensive coverage of multivariate data analysis fundamentals.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
21 May 2020
Listed Since
26 February 2020

Barcode

No barcode data available

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