Analysis of Multivariate and High-Dimensional Data

Book Details:

• Publisher: Cambridge University Press

• Author: Koch

• Language: English

• Edition: 1

• ISBN: 9780521887939

• Pages: 504

• Cover: Hardcover

• Dimensions: 10.1 x 7.0 x 1.2 inches

About The Book:

"Big Data: Statistical Analysis and Machine Learning", written by Koch, is a modern and comprehensive text designed to bridge the gap between classical multivariate methods and the contemporary techniques emerging from machine learning and engineering. It equips students and professionals for navigating the world of big data, integrating both theoretical and practical approaches to statistical learning.

The book lays out a clear theoretical framework, offering formal statements that define the “safe operating zone” for the methods discussed. This helps readers understand when and how to apply the techniques effectively and assess the suitability of their data. The text also includes numerous examples from diverse fields such as medicine, biology, marketing, finance, and bioinformatics, making it highly applicable to real-world problems. High-dimensional, low-sample-size data is given special attention, ensuring that the reader is well-prepared to handle complex datasets.

This textbook is richly illustrated with color, algorithms, Matlab code, and problem sets, providing both depth and clarity. It is particularly suitable for master’s and graduate students in statistics, as well as researchers working in data-intensive disciplines.

By revisiting several datasets and comparing methods throughout, this text fosters a hands-on understanding of the strengths and limitations of different approaches. Whether you are new to the field or a seasoned researcher, this book will provide you with a robust framework for working with big data and statistical analysis.