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Reading list
We've selected 11 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Multiple Testing Problem.
Provides a comprehensive overview of multiple hypothesis testing procedures, including both theoretical and practical aspects.
Provides a comprehensive overview of statistical hypothesis testing, including multiple hypothesis testing.
Provides a comprehensive overview of multiple hypothesis testing, covering both the theoretical foundations and practical applications. It valuable resource for researchers who need to understand the latest developments in the field.
Provides a comprehensive overview of multiple testing, covering both the theoretical foundations and practical applications. It valuable resource for researchers who need to understand the latest developments in the field.
Provides a practical guide to multiple hypothesis testing, covering both basic and advanced methods.
Provides a practical guide to multiple comparisons in clinical research. It covers a wide range of topics, including the Benjamini-Hochberg procedure, the Bonferroni correction, and the false discovery rate.
Provides a practical guide to multiple hypothesis testing in R. It covers a wide range of topics, including the Benjamini-Hochberg procedure, the Bonferroni correction, and the false discovery rate.
Provides a comprehensive overview of multiple testing in genomic sequencing. It covers a wide range of topics, including the Benjamini-Hochberg procedure, the Bonferroni correction, and the false discovery rate.
Provides a comprehensive overview of multiple testing in finance. It covers a wide range of topics, including the Benjamini-Hochberg procedure, the Bonferroni correction, and the false discovery rate.
Provides an overview of multiple comparison methods in the context of clinical research and discusses the practical considerations for designing and analyzing clinical trials.
Focuses on the practical application of multiple testing methods in clinical research and provides guidance on how to avoid common pitfalls.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/t1d4cb/multiple
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