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Behavioral Social Choice: Probabilistic Models, Statistical Inference, and Applications
Behavioral Social Choice: Probabilistic Models, Statistical Inference, and Applications
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Statistical and Probabilistic Methods in Actuarial Science (Chapman & Hall/CRC Series in Actuarial Science)
Statistical and Probabilistic Methods in Actuarial Science (Chapman & Hall/CRC Series in Actuarial Science)
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Bayesian Analysis with Python - Second Edition: Introduction to statistical modeling and probabilistic programming using PyMC3 and ArviZ
Bayesian Analysis with Python - Second Edition: Introduction to statistical modeling and probabilistic programming using PyMC3 and ArviZ
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Heavy-Tail Phenomena: Probabilistic and Statistical Modeling (Springer Series in Operations Research and Financial Engineering)
Heavy-Tail Phenomena: Probabilistic and Statistical Modeling (Springer Series in Operations Research and Financial Engineering)
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Probabilistic and Statistical Aspects of Quantum Theory: 1 (Publications of the Scuola Normale Superiore, 1)
Probabilistic and Statistical Aspects of Quantum Theory: 1 (Publications of the Scuola Normale Superiore, 1)
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BAYESIAN INFERENCE WITH PYTHON FOR BEGINNERS: An Introductory, Hands-On Guide to Probabilistic Modeling and Statistical Reasoning Using PyMC and NumPy.
BAYESIAN INFERENCE WITH PYTHON FOR BEGINNERS: An Introductory, Hands-On Guide to Probabilistic Modeling and Statistical Reasoning Using PyMC and NumPy.
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Statistical Hypothesis Testing in Context: Volume 52: Reproducibility, Inference, and Science: Series Number 52 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 52)
Statistical Hypothesis Testing in Context: Volume 52: Reproducibility, Inference, and Science: Series Number 52 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 52)
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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)
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 Principles for the Design of Experiments: Applications to Real Experiments: 36 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 36)
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 & 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)
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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Confidence, Likelihood, Probability – Statistical Inference with Confidence Distributions
Confidence, Likelihood, Probability – Statistical Inference with Confidence Distributions
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STATORY ANALYTICS LANGUAGE FOUNDATIONS: Declarative Statistical Modeling for Inference Simulation and Large-Scale Analysis (Statistical, Probabilistic & Analytical Computing)
STATORY ANALYTICS LANGUAGE FOUNDATIONS: Declarative Statistical Modeling for Inference Simulation and Large-Scale Analysis (Statistical, Probabilistic & Analytical Computing)
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Statistical Models – Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 11
Statistical Models – Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 11
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PROBABILIS COMPUTATION FOR STOCHASTIC SYSTEMS: Programming Uncertainty Randomness and Probabilistic Decision Models (Statistical, Probabilistic & Analytical Computing)
PROBABILIS COMPUTATION FOR STOCHASTIC SYSTEMS: Programming Uncertainty Randomness and Probabilistic Decision Models (Statistical, Probabilistic & Analytical Computing)
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Statistical Analysis of Stochastic Processes in Time – Cambridge University Press Series No. 14
Statistical Analysis of Stochastic Processes in Time – Cambridge University Press Series No. 14
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Statistical Mechanics of Disordered Systems: A Mathematical Perspective (Cambridge Series No. 18)
Statistical Mechanics of Disordered Systems: A Mathematical Perspective (Cambridge Series No. 18)
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Mathematical Foundations of Infinite-Dimensional Statistical Models – Vol. 40
Mathematical Foundations of Infinite-Dimensional Statistical Models – Vol. 40
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Mathematical Foundations of Infinite-Dimensional Statistical Models: Series Number 40 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 40)
Mathematical Foundations of Infinite-Dimensional Statistical Models: Series Number 40 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 40)
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The Emergence of Probability: A Philosophical Study of Early Ideas About Probability Induction and Statistical Inference (Cambridge Series on Statistical & Probabilistic Mathematics)
The Emergence of Probability: A Philosophical Study of Early Ideas About Probability Induction and Statistical Inference (Cambridge Series on Statistical & Probabilistic Mathematics)
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Essentials of Statistical Inference
Essentials of Statistical Inference
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Modern Discrete Probability: An Essential Toolkit (Cambridge Series in Statistical and Probabilistic Mathematics)
Modern Discrete Probability: An Essential Toolkit (Cambridge Series in Statistical and Probabilistic Mathematics)
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Modern Statistical Methods and Theory: An Introduction to Nonparametric and High-Dimensional Statistics (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 60)
Modern Statistical Methods and Theory: An Introduction to Nonparametric and High-Dimensional Statistics (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 60)
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Predictive Statistics – Analysis and Inference beyond Models – Cambridge University Press
Predictive Statistics – Analysis and Inference beyond Models – Cambridge University Press
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Markov Chains – Cambridge Series in Statistical and Probabilistic Mathematics, Series No. 2
Markov Chains – Cambridge Series in Statistical and Probabilistic Mathematics, Series No. 2
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Probability on Trees and Networks: 42 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 42)
Probability on Trees and Networks: 42 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 42)
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Empirical Processes in M-Estimation: 6 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 6)
Empirical Processes in M-Estimation: 6 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 6)
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Spectral Analysis for Univariate Time Series: 51 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 51)
Spectral Analysis for Univariate Time Series: 51 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 51)
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Numerical Methods of Statistics: 32 (Cambridge Series in Statistical and Probabilistic Mathematics)
Numerical Methods of Statistics: 32 (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)
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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Design of Comparative Experiments: 25 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 25)
Design of Comparative Experiments: 25 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 25)
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Asymptotic Statistics - Cambridge Series in Statistical & Probabilistic Mathematics, No. 3
Asymptotic Statistics - Cambridge Series in Statistical & Probabilistic Mathematics, No. 3
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Fundamentals of Nonparametric Bayesian Inference: 44 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 44)
Fundamentals of Nonparametric Bayesian Inference: 44 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 44)
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Probability: Theory and Examples: 49 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 49)
Probability: Theory and Examples: 49 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 49)
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A User's Guide to Measure Theoretic Probability – Cambridge University Press – Series No. 8
A User's Guide to Measure Theoretic Probability – Cambridge University Press – Series No. 8
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Random Graphs and Complex Networks (Cambridge Series in Statistical and Probabilistic Mathematics)
Random Graphs and Complex Networks (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)
Bootstrap Methods And Their Application: 1 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 1)
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High-Dimensional Probability – An Introduction with Applications in Data Science
High-Dimensional Probability – An Introduction with Applications in Data Science
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A User's Guide to Measure Theoretic Probability: 8 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 8)
A User's Guide to Measure Theoretic Probability: 8 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 8)
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Bayesian Nonparametrics – Cambridge Series in Statistical and Probabilistic Mathematics No. 28
Bayesian Nonparametrics – Cambridge Series in Statistical and Probabilistic Mathematics No. 28
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High-Dimensional Probability: An Introduction with Applications in Data Science (Cambridge Series in Statistical and Probabilistic Mathematics)
High-Dimensional Probability: An Introduction with Applications in Data Science (Cambridge Series in Statistical and Probabilistic Mathematics)
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