eBooks
Diabetes and Obesity
Epidemiology
- Blog: R! books
- CDC: Epidemiology Training & Resources
- The CDC Field Epidemiology Manual
- CDC (2012). Principles of Epidemiology in Public Health Practice, 3rd ed.
- CDC (2015). Epidemiology and Prevention of Vaccine-Preventable Disease, "Pink book webinar series", and the pdf file of the Pink book
- Preedy (2010): Handbook of disease b burdens and quality of life measures
- Neale Batra: R for applied epidemiology and public health
- Pearl: Causal Inference in Statistics: A Primer
- Hernan (2017).Causal Inference Book
- Nick Huntington-Klein: The Effect
- Harper (2005). Methods for Measuring Cancer Disparities monograph
- Hyndman. Forecasting: principles and practice (Generating quantile forecasts in R)
- Bullard (2011). A Brief Introduction to Bayesian Statistics, Talk of NCSSM Department of Mathematics.
- Teague (2004). The Gini Index: Measuring Inequity
- O'Donnell (2008). Analyzing Health Equity Using Household Survey Data. This book used Stata doing the analyses. On the same website, there is an introduction of ADePT: Software Platform for Automated Economic Analysis, a freeware from the World Bank.
- Burton-Jeangros (2015 SpringerOpen). A life course perspective on health trajectories and transitions
- Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease by Institute of Medicine
- Social Research Methods: This website is for people involved in applied social research and evaluation. You'll find lots of resources and links to other locations on the Web that deal in applied social research methods.
- Resources of disability research
- ACS 2018: Understanding and Using American Community Survey Data: What All Data Users Need to Know
- Gary King (2004): Ecological Inference New Methodological Strategies
- Russell Poldrack: Statistical Thinking for the 21st Century
- Parker (2017).National Center for Health Statistics Data Presentation Standards for Proportions
- Huff (1954). How to lie with statistics
- Free Statistics book collected by FreeTechBooks
- Hyndman & Athanasopolos. Forecasting: principles and practice (book notes) (using R!)
- Swinscow. Statistics at Square One - BMJ
- Cosma Shalizi: Advanced Data Analysis from an Elementary Point of View
- Lance (2014). How do we know if a prog4ram made a difference? A guide to statistical methods for program impact evaluation (using Stata) (pdf)
- Norm Matloff:From Algorithms to Z-Scores: Probabilistic and Statistical Modeling in Computer Science (R!)
- Shalizi (2016).Advanced Data Analysis from an Elementary Point of View (draft)
- Stephen Jenkins. Survival Analysis with Stata - University of Essex
- IARC Scientific Publication (Selected)
- Breslow (1980): Statistical Methods in Cancer Research Volume I: The Analysis of Case-Control Studies
- Breslow (1986): Statistical Methods in Cancer Research Volume II: The Design and Analysis of Cohort Studies
- Krewski (1986): Statistical Methods in Cancer Research Volume III: The Design and Analysis of Long-term Animal Experiments
- Esteve (1994): Statistical Methods in Cancer Research Volume IV: Descriptive Epidemiology
- Gary Oehlert (2010).A First Course in Design and Analysis of Experiments
- Statistics in Medicine: Tutorial papers from Statistics in Medicine for FREE (before 12/31/17)
- Statsoft
- Engineering Statistics Handbook
- Reliability Engineering Resource Web Site
- Analytic Methods in Maternal and Child Health has a chapter about Methods for Analyzing Trend Data
- Train (2002). Discrete Choice Methods with Simulation (pdf), which is referred by Luedicke in "Flexible discrete choice modeling using a multinomial probit model" using Stata. A blog about Discrete Choice Analysis and a Wikipedia article
- Kuhfeld. Discrete Choice (pdf) using SAS [discrete choice analysis is a statistical technique for modeling trade-offs such as consumers make between the features and the price of a good or service. Results of this analysis indicate what features may be added, eliminated, or enhanced, and how the different versions of the same item may sold at different price levels.]
- Simon Wood: Core Statistics (pdf) for anyone starting a statistics PhD
- HyperStat Online: An introductory statistics textbook and online tutorial for help in statistics courses
- AP Statistics Curriculum 2007
- CurveFit: a guideline of nonlinear regression in GraphPad library.
- National Guideline Clearinghouse
- IARC Publications - there are a few good books about statistical methods
- Berger (1988). The likelihood principle: a review, generalizations, and statistical implications (from Institute of Mathematical Statistics Lecture Notes - Monograph Series (free) on Euclid)
- Sgro: Tabular data analysis with R and Tidyverse (How to Use Survey Weights in R by Mike Burke)
- Open Textbook Library supported by the Center for Open Education and the Open Textbook Network
- Diez (2004): Introductory Statistics with Randomization and Simulation 1st
- Blais (2017): Statistical Inference for Everyone
Data Science
- Boehmke: Hands-On Machine Learning with R (Interpretable Machine Learning)
- Molnar (2021): Interpretable Machine Learning - A Guide for Making Black Box Models Explainable
- Burkov: Machine Learning Engineering
- Burkov: The Hundred-Page Machine Learning Book
- Peng: R Programming for Data Science
- Max Welling (2011). A First Encounter with Machine Learning
- Efron & Hastie (2016): Computer Age Statistical Inference: Algorithms, Evidence and Data Science
- Pear (2018): The Seven Pillars of Causal Reasoning with Reflections on Machine Learning
- Gareth James (2013), Trevor Hastie, Robert Tibshirani, Daniela Witten: An Introduction to Statistical Learning, with Applications in R, 2nd. pdf) with the excellent self-paced video training course. (here is the 15-hours of video training video abstracted by the Data School (YouTube))
- Trevor Hastie (2009): The Elements of Statistical Learning: Data Mining, Inference, and Prediction. This book is not an easy read book without strong mathematical knowledge.
- Ian Goodfellow: Deep Learning - a MIT Press book
- Deisenroth (2020):Mathematics for Machine Learning
- Bishop (2006): Pattern Recognition and Machine Learning
- Barber. Bayesian Reasoning and Machine Learning. This is a book for a person with little background in math and probabilistic methods.
- John Paisley (2016): Course notes for Bayesian models for machine learning
- Bernhard Scholkopf (2019): Causality for machine learning
- Blum: Foundations of Data Science
- Silge: Text Mining with R
- Kroese: Data Science & Machine Learning: Mathematical and Statistical Methods (Python)
- Introduction to Earth Data Science (Python) Jupyter For Python (Code and Markdown)
- R Interface to Python (reticulate)
- Monarch: Human-in-the-Loop Machine Learning
Mathematics
Econometrics
- Grinstead: Introduction to Probability
- Pishro-Nik (2014): Introduction to Probability, Statistics, and Random Processes (video)
- Thompson(1914): Calculus Made Easy, 2nd, Project Gutenberg version
- Strang (1991). Calculus (MIT)
- Boyd: Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares
- 3Blue1Brown: Essence of mathematics
- Hefferon: Linear Algebra
- Mathews (1991): Elementary Linear Algebra
- A First Course in Linear Algebra
- Wilke: Fundamentals of Data Visualization from the Serial Mentor
Econometrics
- Bruce Hansen: Introduction to Econometrics and Econometrics
- Hanck: Introduction to Econometrics with R (pdf)
- Colonescu: Principles of Econometrics with R (pdf)
- Robinson: 10 Fundamental Theorems for Econometrics (Delta Method in Plain English)
Others
- CDC Crisis & Emergency Risk Communication Manual and Tools
- FreeTechBooks: more related to computer science, engineering and programming
- LibriVox, the free public domain audiobooks
- Schulz. Why using the greedy.* in regular expression is almost never what you actually want
- The art of scientific investigation (1957)
- Free Kindle book updates
- Free eBook Collections - Free classics and out-of-copyright, pre-1923 books, as well as limited-time free promotional ebooks available for Kindle.
- Free Kindle Books offers Free Classic E-Books in Kindle-compatible MOBI and PRC formats.
- Project Gutenberg is the place where you can download over 33,000 free ebooks to read on your PC, iPad, Kindle, Sony Reader, iPhone, Android or other portable device.
- ManyBooks.net There are more than 29,000 eBooks available here and they're all free!
- FreeBookSpot FreeBookSpot is an online source of free ebooks download with 4485 FREE E-BOOKS in 96 categories
- BookYards is a web portal in which books, education materials, information, and content will be freely to anyone who has an internet connection.
- Free Ebook (need register as a member)
- Apprentice Alf's Blog about DRM. Online eBook Converter
