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Springer Multiple Testing Procedures with Applications to Genomics

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Description

This comprehensive guide from Springer explores the theoretical foundations of multiple testing methods and their practical application across genomics research. The book systematically covers statistical approaches to handling multiple hypothesis tests, a critical challenge in genomic data analysis where researchers often examine thousands of variables simultaneously. By addressing both foundational theory and real-world implementation, this resource helps statisticians and genomic researchers understand when and how to apply different testing procedures to control error rates whilst maintaining statistical power. The applications to genomics demonstrate how these methods solve specific problems encountered in gene expression analysis, association studies, and other high-dimensional biological investigations. Part of the respected Springer Series in Statistics, this volume bridges the gap between theoretical statistics and practical genomic research.

Key Features

Detailed theoretical foundations of multiple testing methods suitable for advanced statistics and genomics study.

Applications to genomics including gene expression analysis and association studies with real-world examples.

Part of the Springer Series in Statistics, providing authoritative and peer-reviewed content on statistical methodology.

Comprehensive coverage of error rate control and statistical power considerations in hypothesis testing scenarios.

Practical guidance on selecting and implementing appropriate testing procedures for high-dimensional biological data.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
25 November 2010
Listed Since
01 October 2010

Barcode

No barcode data available

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