Cause and Correlation in Biology
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Abstract
Many problems in biology require an understanding of the relationships among variables in a multivariate causal context. Exploring such cause-effect relationships through a series of statistical methods, this book explains how to test causal hypotheses when randomised experiments cannot be performed. This completely revised and updated edition features detailed explanations for carrying out statistical methods using the popular and freely available R statistical language. Sections on d-sep tests, latent constructs that are common in biology, missing values, phylogenetic constraints, and multilevel models are also an important feature of this new edition. Written for biologists and using a minimum of…
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Topics
Keywords
- Jargon
- Multivariate statistics
- Path analysis (statistics)
- Statistical hypothesis testing
- Context (archaeology)
- Computer science
- Data science
- Statistics
UN Sustainable Development Goals
- Quality Education
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