Supported by a wealth of learning features, exercises, and visual
elements as well as online video tutorials and interactive
simulations, this book is the first student-focused introduction to
Bayesian statistics. Without sacrificing technical integrity for
the sake of simplicity, the author draws upon accessible,
student-friendly language to provide approachable instruction
perfectly aimed at statistics and Bayesian newcomers. Through a
logical structure that introduces and builds upon key concepts in a
gradual way and slowly acclimatizes students to using R and Stan
software, the book covers: An introduction to probability and
Bayesian inference Understanding Bayes' rule Nuts and bolts of
Bayesian analytic methods Computational Bayes and real-world
Bayesian analysis Regression analysis and hierarchical methods This
unique guide will help students develop the statistical confidence
and skills to put the Bayesian formula into practice, from the
basic concepts of statistical inference to complex applications of
analyses.
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