|
Showing 1 - 2 of
2 matches in All Departments
To date, statistics has tended to be neatly divided into two
theoretical approaches or frameworks: frequentist (or classical)
and Bayesian. Scientists typically choose the statistical framework
to analyse their data depending on the nature and complexity of the
problem, and based on their personal views and prior training on
probability and uncertainty. Although textbooks and courses should
reflect and anticipate this dual reality, they rarely do so. This
accessible textbook explains, discusses, and applies both the
frequentist and Bayesian theoretical frameworks to fit the
different types of statistical models that allow an analysis of the
types of data most commonly gathered by life scientists. It
presents the material in an informal, approachable, and progressive
manner suitable for readers with only a basic knowledge of calculus
and statistics. Statistical Modeling with R is aimed at senior
undergraduate and graduate students, professional researchers, and
practitioners throughout the life sciences, seeking to strengthen
their understanding of quantitative methods and to apply them
successfully to real world scenarios, whether in the fields of
ecology, evolution, environmental studies, or computational
biology.
Determining the scientific relationship between biodiversity and ecosystem functioning has now emerged as one of the most important challenges in ecological and environmental science. This book provides a timely synthesis and critical assessment in order to generate a consensus on the main issues involved and stimulate new perspectives for future research.
|
|
Email address subscribed successfully.
A activation email has been sent to you.
Please click the link in that email to activate your subscription.