All | (Big) Data Analytics | Algorithms | Artificial Intelligence | Bayesian Networks | Business & Strategy | Computer Vision | Data Journalism | Data Mining | Data Scientists | Data Structures | Data Visualization | General Data Science | Hadoop, MapReduce | Information Retrieval | Linear Regression | Linguistic | Machine Learning, Predictive Analytics | Math | Metadata | Natural Language Processing | Network Science | Other Sites with Free Data Science Resources | Probability | Python | R | Singularity/Transhumanism | Statistics | Text MiningIntroductory Statistics with Randomization and Simulation.
An Introduction to Statistical Learning with Applications in R.
Probability and Statistics Cookbook.
Think Stats: Exploratory Data Analysis in Python. An introduction to the practical tools of exploratory data analysis
Machine Learning, Neural and Statistical Classification.
Statistical foundations of machine learning. Statistical foundations of machine learning intended as the discipline which deals with the automatic design of models from data
STATISTICS Methods and Applications. A nearly encyclopedic comprehensive presentationof statistical methods and analytic approaches used in science, industry, business, and data mining written from the perspective of the real-life practitioner
simpleR - Using R for Introductory Statistics. How to use R while learning introductory statistics
Analyzing Linguistic Data: A practical introduction to statistics. Statistical analysis of language, designed for linguists with a non-mathematical background
OpenIntro Statistics. Foundation of statistical thinking and methods
A Practitioner's Guide to Generalized Linear Models. Written for the practising actuary who would like to understand generalized linear models (GLMs) and use them to analyze insurance data
Introduction to Statistical Thought. A focus on ideas that statisticians care about as opposed to technical details of how to put those ideas into practice
The Elements of Statistical Learning (Data Mining, Inference and Prediction). Bringing together many new ideas in learning and explaining them in a statistical framework
Think Stats: Probability and Statistics for Beginners. Emphasizes the use of statistics and a computational approach to explore large datasets
Statistics with R. Notes author took while discovering and using the statistical environment R
Collaborative Statistics. An introductory statistics course for students majoring in fields other than engineering or math. The only prerequisite is intermediate algebra
Concepts and Applications of Inferential Statistics. A full-length and occasionally interactive statistics textbook.
An Introduction to Statistical Learning (with applications in R). For those wishing to use statistical learning tools to analyze their data
Statistics by Wikibooks.org. Modern statistics and some practical applications of statistics
Think Bayes: Bayesian Statistics Made Simple. Bayesian statistics with Python and discrete approximations