Statistics is concerned with investigating the degree of confidence we can have in various hypotheses. The Bayesian approach is distinguished by giving each hypothesis a probability and then modifying it in light of the experimental data. This is controversial because for a new theory with no data available, an element of guesswork has to be involved. The author presents the ideas behind Bayesian statistics at a level suitable for advanced undergraduate or postgraduate students. The discrepancies between the conclusions of Bayesian and classical statistics are highlighted.
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Clear introduction to Bayesian statistics for serious learners.
Who is this book for?
If you're curious about modern statistical methods, this book offers a comprehensive look at Bayesian statistics, perfect for students or anyone wanting to deepen their understanding. The way it explains updating probabilities with new data makes complex ideas more approachable, even for those new to the subject. You'll appreciate how it contrasts Bayesian and classical approaches, giving you a rounded perspective on statistical inference.
