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The statistical analyses that students of the life-sciences are being expected to perform are becoming increasingly advanced. Whether at the undergraduate, graduate, or post-graduate level, this book provides the tools needed to properly analyze your data in an efficient, accessible, plainspoken, frank, and occasionally humorous manner, ensuring that readers come away with the knowledge of which analyses they should use and when they should use them. The book uses the statistical language R, which is the choice of ecologists worldwide and is rapidly becoming the 'go-to' stats program throughout the life-sciences. Furthermore, by using a single, real-world dataset throughout the book, readers...
This book uses the statistical language R, which is the choice of ecologists worldwide and is rapidly becoming the 'go-to' stats program throughout the life-sciences. Furthermore, by using a single, real-world dataset throughout the book, readers are encouraged to become deeply familiar with an imperfect but realistic set of data. - -
Abstract: Plastic phenotypic responses of organisms to key environmental variables are well documented and ecologically important. Less is known about how these responses depend on additional variables that shape either selection or constraints, particularly interactions between biotic and abiotic factors. I studied how multiple abiotic and biotic factors combine to affect the Neotropical treefrog Dendropsophus ebraccatus through its egg, larval, and adult stages. This rainforest frog lays eggs on vegetation above ponds. Embryos develop for 3-4 days, then hatch and fall into the water. Eggs are highly susceptible to desiccation. Rainfall patterns affect D. ebraccatus egg survival both direct...
Faculties, publications and doctoral theses in departments or divisions of chemistry, chemical engineering, biochemistry and pharmaceutical and/or medicinal chemistry at universities in the United States and Canada.
Measurements like mass, length and speed are "linear"; but compass direction or the time of the year are "circular". Circular data have a repeating nature and an arbitrary zero: 12 months after the 1st of July it is the 1st of July again. This book explains how to easily and effectively analyse circular data statistically.