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Research Methods Using R - Advanced Data Analysis in the Behavioural and Biological Sciences (Paperback)
Loot Price: R976
Discovery Miles 9 760
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Research Methods Using R - Advanced Data Analysis in the Behavioural and Biological Sciences (Paperback)
Expected to ship within 9 - 15 working days
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Providing complete coverage of advanced research methods for
undergraduates, Daniel H. Baker supports students in their mastery
of more advanced research methods and their application in R. This
brand new title brings together coverage of a variety of topics for
readers with basic statistical knowledge. It begins with material
on the fundamental tools - nonlinear curve fitting and function
optimization, stochastic methods, and Fourier (frequency) analysis
- before leading readers on to more specialist content - bivariate
and multivariate statistics, Bayesian statistics, and machine
learning methods. Several chapters also discuss methods that can be
used to improve research practises, including power analysis,
meta-analysis, reproducible data analysis. Written to build a
student's confidence with using R in a step-by-step way, early
chapters present the essentials, ensuring that the content is
accessible to those that have never programmed before. By giving
them a feel for how the software works in practice, students are
gradually introduced to simple examples of techniques before
building up to more detailed implementations demonstrated in worked
examples. Readers are also presented with opportunities to try
analysis techniques for themselves. Practice questions are
presented at the end of each chapter with answer guidance supplied
in the book, while multiple-choice-questions with instant feedback
can be accessed online. The author also provides datasets online
which students can use to practise their new skills. Digital
formats and resources This book is available for students and
institutions to purchase in a variety of formats, and is supported
by online resources. - The e-book offers a mobile experience and
convenient access along with functionality, navigation features,
and links that offer extra learning support. This book is
accompanied by online resources including multiple-choice-questions
with instant feedback, example code, and data files allowing
students to run examples independently.
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