Bayesian Analysis with Python - Second Edition: Introduction to statistical modeling and probabilistic programming using PyMC3 and ArviZ
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Statistical and Probabilistic Methods in Actuarial Science (Chapman & Hall/CRC Series in Actuarial Science)
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Heavy-Tail Phenomena: Probabilistic and Statistical Modeling (Springer Series in Operations Research and Financial Engineering)
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Behavioral Social Choice: Probabilistic Models, Statistical Inference, and Applications
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Probabilistic and Statistical Aspects of Quantum Theory: 1 (Publications of the Scuola Normale Superiore, 1)
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Probabilistic Models for Sports Betting: Mathematical Foundations, Statistical Inference, and Applications Across Sports
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STEP-BY-STEP BAYESIAN STATISTICS: A Beginner’s Guide to Probabilistic Thinking and Statistical Modeling
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Probabilistic and Statistical Methods in Cryptology: An Introduction by Selected Topics
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STEP-BY-STEP BAYESIAN STATISTICS: A Beginner’s Guide to Probabilistic Thinking and Statistical Modeling
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Probabilistic & Statistical Learning How Machines Think When They Are Not Sure: A first-principles, dialogue-driven guide for all ages: 4 (Deep Roots: ... that teaches not just how models work)
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Statistical Hypothesis Testing in Context – Reproducibility, Inference, and Science – Volume 52
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Probabilistic Models for Sports Betting: Mathematical Foundations, Statistical Inference, and Applications Across Sports
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Mathematical Foundations of Infinite-Dimensional Statistical Models – Vol. 40
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Probabilistic & Statistical Learning How Machines Think When They Are Not Sure: A first-principles, dialogue-driven guide for all ages (Deep Roots: ... that teaches not just how models work)
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Statistical Principles for the Design of Experiments: Applications to Real Experiments: 36 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 36)
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Probabilistic Risk Analysis and Bayesian Decision Theory: With Applications in the Environmental Sciences (Textbooks in Statistical Science)
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Mathematical Foundations of Infinite-Dimensional Statistical Models: Series Number 40 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 40)
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Modern Discrete Probability: An Essential Toolkit (Cambridge Series in Statistical and Probabilistic Mathematics)
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Bootstrap Methods And Their Application: 1 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 1)
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Statistical Models – Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 11
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Networks: Probability and Statistics (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 57)
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Empirical Processes in M-Estimation: 6 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 6)
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High-Dimensional Probability – An Introduction with Applications in Data Science
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A User's Guide to Measure Theoretic Probability – Cambridge University Press – Series No. 8
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Design of Comparative Experiments – Cambridge Ser. in Statistical & Probabilistic Mathematics No 25
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Probability: Theory and Examples: 49 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 49)
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Asymptotic Statistics - Cambridge Series in Statistical & Probabilistic Mathematics, No. 3
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Random Graph Dynamics: 20 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 20)
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Brownian Motion: 30 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 30)
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Data Analysis and Graphics Using R: An Example-based Approach (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 10)
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Probability on Trees and Networks: Series Number 42 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 42)
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Random Graphs and Complex Networks (Cambridge Series in Statistical and Probabilistic Mathematics)
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Data Analysis and Graphics Using R: An Example-Based Approach: 10 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 10)
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Spectral Analysis for Univariate Time Series: 51 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 51)
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Predictive Statistics – Analysis and Inference beyond Models – Cambridge University Press
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High-Dimensional Probability: An Introduction with Applications in Data Science (Cambridge Series in Statistical and Probabilistic Mathematics)
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