books by subject
Mathematical Probability & Statistics

Modular Maths for Edexcel 2nd Edition Statistics 1: Bk. 1 (Modular Maths for Edexcel Statistics)

MEI Statistics 2 (MEI Structured Mathematics (A+AS Level))

Introduction to R for Social Scientists: A Tidy Programming Approach (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)

Heavy-Tail Phenomena: Probabilistic and Statistical Modeling (Springer Series in Operations Research and Financial Engineering)

An Introduction to Copulas (Springer Series in Statistics)

Pattern Recognition and Machine Learning (Information Science and Statistics) (Information Science and Statistics)

Bayesian Computation with R (Use R)

Lattice: Multivariate Data Visualization with R (Use R!)

Introductory Statistics with R (Statistics and Computing)

Introductory Time Series with R (Use R!)

A History of Numerical Analysis from the 16th through the 19th Century: 2 (Studies in the History of Mathematics and Physical Sciences)

Brownian Motion (Stochastic Modelling and Applied Probability)

Applied Bayesian and Classical Inference: The Case of The Federalist Papers (Springer Series in Statistics)

Tools for Statistical Inference: Methods for the Exploration of Posterior Distributions and Likelihood Functions (Lecture Notes in Statistics)

Multivariate Statistical Modelling Based on Generalized Linear Models (Undergraduate Texts in Mathematics)

Activity-Based Statistics: Student Guide (Textbooks in Mathematical Sciences)

Numerical Bayesian Methods Applied to Signal Processing (Statistics and Computing)

The Statistical Theory of Shape (Springer Series in Statistics)

Mathematical and Statistical Methods for Genetic Analysis (Statistics for Biology and Health)

Applying and Interpreting Statistics: A Comprehensive Guide (Springer Texts in Statistics)

Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach

Bayesian Nonparametrics (Springer Series in Statistics)

Applied Multivariate Analysis

Introduction to Statistics: The Nonparametric Way (Springer Texts in Statistics)

Statistical Models Based on Counting Processes (Springer Series in Statistics)

Large Deviations Techniques and Applications: v.38 (Stochastic Modelling and Applied Probability)

Numerical Linear Algebra for Applications in Statistics (Statistics and Computing)

The Nature of Statistical Learning Theory (Information Science and Statistics)

Time Series Analysis and Its Applications (Springer Texts in Statistics)
