Bayesian Statistics for Beginners: a step-by-step approach

Bayesian Statistics for Beginners: a step-by-step approach

2019 | ISBN: 0198841302, 0198841299 | English | 432 Pages | PDF | 49 MB

Bayesian statistics is currently undergoing something of a renaissance. At its heart is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. It is an approach that is ideally suited to making initial assessments based on incomplete or imperfect information; as that information is gathered and disseminated, the Bayesian approach corrects or replaces the assumptions and alters its decision-making accordingly to generate a new set of probabilities. As new data/evidence becomes available the probability for a particular hypothesis can therefore be steadily refined and revised. It is very well-suited to the scientific method in general and is widely used across the social, biological, medical, and physical sciences. Key to this book's novel and informal perspective is its unique pedagogy, a question and answer approach that utilizes accessible language, humor, plentiful illustrations, and frequent reference to on-line resources.

Bayesian Statistics for Beginners is an introductory textbook suitable for senior undergraduate and graduate students, professional researchers, and practitioners seeking to improve their understanding of the Bayesian statistical techniques they routinely use for data analysis in the life and medical sciences, psychology, public health, business, and other fields.


[Fast Download] Bayesian Statistics for Beginners: a step-by-step approach

Related eBooks:
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
Emotional Design in Human-Robot Interaction: Theory, Methods and Applications
Nonlinear Expectations and Stochastic Calculus under Uncertainty: with Robust CLT and G-Brownian Mot
Blow-Up in Nonlinear Equations of Mathematical Physics : Theory and Methods
Robotic Building
Proof!: How the World Became Geometrical
Path Regularity for Stochastic Differential Equations in Banach Spaces
The Concrete Tetrahedron: Symbolic Sums, Recurrence Equations, Generating Functions, Asymptotic Esti
The Geometry of Information Retrieval
Mathematical Geosciences: Hybrid Symbolic-Numeric Methods
Practical Math Applications
Mastering Mathematics WJEC GCSE Practice Book: Higher
Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.