Acabei de saber na lista de emails da Associação Brasileira de Estatística que a editora Springer disponibilizou mais de 500 livros gratuitamente. Basta visitar o site e baixar, sem sequer necessitar fazer cadastro. A lista completa de livros está nesta planilha do Excel, mas abaixo eu coloquei a listagem de livros de Matemática e Estatística, colocados em ordem alfabética do título. Aproveitem.
- A Beginner’s Guide to R - Alain Zuur, Elena N. Ieno, Erik Meesters
- A Modern Introduction to Probability and Statistics - F.M. Dekking, C. Kraaikamp, H.P. Lopuhaä, L.E. Meester
- A Primer on Scientific Programming with Python - Hans Petter Langtangen
- A Pythagorean Introduction to Number Theory - Ramin Takloo-Bighash
- Abstract Algebra - Gregory T. Lee
- Algebra - Serge Lang
- All of Statistics - Larry Wasserman
- An Introduction to Statistical Learning - Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
- Applied Linear Algebra - Peter J. Olver, Chehrzad Shakiban
- Applied Multivariate Statistical Analysis - Wolfgang Karl Härdle, Léopold Simar
- Applied Partial Differential Equations - J. David Logan
- Applied Predictive Modeling - Max Kuhn, Kjell Johnson
- Applied Quantitative Finance - Wolfgang Karl Härdle, Cathy Yi-Hsuan Chen, Ludger Overbeck
- Bayesian and Frequentist Regression Methods - Jon Wakefield
- Bayesian Essentials with R - Jean-Michel Marin, Christian P. Robert
- Brownian Motion, Martingales, and Stochastic Calculus - Jean-François Le Gall
- Business Statistics for Competitive Advantage with Excel 2016 - Cynthia Fraser (este não está gratuito)
- Calculus With Applications - Peter D. Lax, Maria Shea Terrell
- Classical Fourier Analysis - Loukas Grafakos
- Complex Analysis - Joseph Bak, Donald J. Newman
- Design and Analysis of Experiments - Angela Dean, Daniel Voss, Danel Draguljić
- Differential Equations and Their Applications - Martin Braun
- Discrete Mathematics - László Lovász, József Pelikán, Katalin Vesztergombi
- Elementary Analysis - Kenneth A. Ross
- Fundamentals of Clinical Trials - Lawrence M. Friedman, Curt D. Furberg, David L. DeMets, David M. Reboussin, Christopher B. Granger
- Introduction to Partial Differential Equations - David Borthwick
- Introduction to Partial Differential Equations - Peter J. Olver
- Introduction to Smooth Manifolds - John Lee
- Introduction to Statistics and Data Analysis - Christian Heumann, Michael Schomaker, Shalabh
- Introduction to Time Series and Forecasting - Peter J. Brockwell, Richard A. Davis
- Introductory Statistics with R - Peter Dalgaard
- Introductory Time Series with R - Paul S.P. Cowpertwait, Andrew V. Metcalfe
- Linear Algebra - Jörg Liesen, Volker Mehrmann
- Linear Algebra Done Right - Sheldon Axler
- Methods of Mathematical Modelling - Thomas Witelski, Mark Bowen
- Modeling Life - Alan Garfinkel, Jane Shevtsov, Yina Guo
- Multivariate Calculus and Geometry - Seán Dineen
- Numerical Optimization - Jorge Nocedal, Stephen Wright
- Ordinary Differential Equations - William A. Adkins, Mark G. Davidson
- Partial Differential Equations - Jürgen Jost
- Probability - Jim Pitman
- Probability Theory - Alexandr A. Borovkov
- Probability Theory - Achim Klenke
- Proofs from THE BOOK - Martin Aigner, Günter M. Ziegler
- Quantum Theory for Mathematicians - Brian C. Hall
- Reading, Writing, and Proving - Ulrich Daepp, Pamela Gorkin
- Real Analysis - Miklós Laczkovich, Vera T. Sós
- Regression Modeling Strategies - Frank E. Harrell , Jr.
- Representation Theory - William Fulton, Joe Harris
- Statistical Analysis and Data Display - Richard M. Heiberger, Burt Holland
- Statistical Learning from a Regression Perspective - Richard A. Berk
- Statistics and Data Analysis for Financial Engineering - David Ruppert, David S. Matteson
- Survival Analysis - David G. Kleinbaum, Mitchel Klein
- The Elements of Statistical Learning - Trevor Hastie, Robert Tibshirani, Jerome Friedman
- Time Series Analysis - Jonathan D. Cryer, Kung-Sik Chan
- Understanding Analysis - Stephen Abbott
- Understanding Statistics Using R - Randall Schumacker, Sara Tomek