Everything is Predictable : How Bayes' Remarkable Theorem Explains the World
Tom Chivers
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The Random Factor : How Chance and Luck Profoundly Shape Our Lives and the World around Us
Prof. Mark Robert Rank
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Probably Overthinking It : How to Use Data to Answer Questions, Avoid Statistical Traps, and Make Better Decisions
Allen B. Downey
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How to Expect the Unexpected : The Science of Making Predictions and the Art of Knowing When Not To
Kit Yates
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Model-Based Machine Learning
John (Microsoft Research Ltd., Cambridge, United Kingdom) Winn
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Graph Theory and Additive Combinatorics : Exploring Structure and Randomness
Yufei (Massachusetts Institute of Technology) Zhao
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An Introduction to R and Python for Data Analysis : A Side-By-Side Approach
Taylor R. (University of Virginia) Brown
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Modelling Survival Data in Medical Research
David (UK Transplant, Bristol, UK) Collett
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Nonparametric Statistical Methods Using R
John Kloke
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An Introduction to Spatial Data Science with GeoDa : Volume 2: Clustering Spatial Data
Luc (University of Chicago) Anselin
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Bayesian Precision Medicine
Peter F. (M.D. Anderson Cancer Center, Houston, Texas, USA) Thall
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Generalized Linear Mixed Models : Modern Concepts, Methods and Applications
Walter W. Stroup
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A Practical Guide to Data Analysis Using R : An Example-Based Approach
John H. (Statistics Research Associates, Wellington, New Z Maindonald
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Generalized Additive Models for Location, Scale and Shape : A Distributional Regression Approach, with Applications
Mikis D. (University of Greenwich) Stasinopoulos
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Matrix Algebra : Theory, Computations and Applications in Statistics
James E. Gentle
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Time Series Analysis
James D. Hamilton
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The Elements of Statistical Learning : Data Mining, Inference, and Prediction, Second Edition
Trevor Hastie
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Statistical Inference
Roger (Arizona State University) Berger
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A Modern Introduction to Probability and Statistics : Understanding Why and How
F.M. Dekking
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The Practice of Statistics
Daren Starnes
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Elementary Stochastic Calculus, With Finance In View
Thomas (Univ Of Copenhagen, Denmark) Mikosch
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Monte Carlo Methods in Financial Engineering
Paul Glasserman
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Doing Bayesian Data Analysis : A Tutorial with R, JAGS, and Stan
John (Indiana University, Bloomington, USA) Kruschke
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