Foundations of Bayesian Statistics for Data Scientists: With R and Python (Chapman & Hall/CRC Texts in Statistical Science)
by Alan Agresti, Maria Kateri, Ranjini Grove, Antonietta Mira
Foundations of Bayesian Statistics for Data Scientists presents core Bayesian ideas for modern data analysis. Designed for readers who use R and Python, it combines statistical foundations with computational practice and serves as a reference or learning resource in data science and statistical science.
About This Book
Foundations of Bayesian Statistics for Data Scientists introduces Bayesian statistical thinking for readers working with data.
The book focuses on foundational concepts and methods in Bayesian statistics.
Examples and applications use R and Python, supporting practical learning and computational work.
Written by Alan Agresti, Maria Kateri, Ranjini Grove, and Antonietta Mira, this volume is part of the Chapman & Hall/CRC Texts in Statistical Science series.
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