£64.84

Springer Fundamentals of High-Dimensional Statistics Textbook

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Description

Master the essentials of modern data science with the Fundamentals of High-Dimensional Statistics by Springer. This textbook offers a step-by-step introduction to the core tools and principles required to navigate high-dimensional data environments. Designed for beginning graduate and advanced undergraduate students in statistics and biostatistics, the text provides a clear path through complex topics. Readers will gain a deep understanding of high-dimensional linear regression, graphical models, and inference. The book balances theoretical foundations with practical application, ensuring you can apply these concepts to real-world datasets. To support your learning, each chapter includes numerous exercises, many of which come with detailed solutions to help you verify your progress. Beyond theory, this resource includes computer labs in R. These labs provide practical insights that bridge the gap between mathematical concepts and computational execution. With suggestions for further reading included, this book serves as a comprehensive starting point for anyone looking to build a strong foundation in high-dimensional statistical methods.

Key Features

Comprehensive coverage of high-dimensional linear regression, graphical models, and statistical inference for a complete learning experience.

Hands-on R computer labs included to help you gain practical insights and apply statistical theories to real data.

Extensive collection of chapter exercises, many featuring detailed solutions to support your study and self-assessment.

Designed specifically for beginning graduate and advanced undergraduate students in statistics and biostatistics.

Step-by-step instructional approach that makes complex high-dimensional statistical principles accessible to new learners.

Includes curated suggestions for further reading to help you expand your knowledge beyond the core text.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
18 November 2022
Listed Since
21 October 2022

Barcode

No barcode data available

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