Free books to study Statistics for Data Science
Find a collection of free books to learn about statistics, data analysis, and Data Analytics using Python, R, SAS.
Do you want to learn data analysis and don’t you have enough knowledge about statistics? The following books can be great help. All of them are in English and you have direct download
1.Think Stats, Second Edition:
The notion of this book is that data united with practical systems can answer questions and guide decisions under uncertainty. This book teaches basic statistics with Python and the exploration analysis process and basic data analysis, with a focus on programs rather than mathematics.
https://greenteapress.com/wp/think-stats-2e/
2. Bayesian Methods for Hackers:
This book explains how to apply Bayesian inference methods for programmers who are not so knowledgeable in statistics and mathematics, focused on the programming side.
http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/
3. The Elements of Statistical Learning:
“We are inundated with information but dry with knowledge” — Rutherford D. Roger
This sentence that opens the book explains the need to understand and correctly apply statistical methods of data analysis to understand the world well, given the explosion of information that we are seeing thanks to the digitalization of all industries and sciences. The book focuses on the methods of analysis and their conceptual underpinnings rather than the mathematical details.
https://hastie.su.domains/ElemStatLearn/
4. An Introduction to Statistical Learning:
It is aimed at people who did not study anything related to mathematics (like most programmers), to introduce them to practical statistical learning, inspired by the book. This book is suitable for people with no background in either statistics or computer science. Use R to learn the concepts.
http://faculty.marshall.usc.edu/gareth-james/
5.From Algorithms to Z Scores
Did you see the about vital character of statistics in programming? The writer of this book is Norm Matloff, Professor of University of California. This book clarifies using probabilistic notions and statistical events in R. Again, a good exercise source for R users. It explains the art of dealing with probabilistic representations and selecting the best one for concluding estimation. It is a highly suggested book (specially for R users).
https://heather.cs.ucdavis.edu/probstatbook
I wish this will help you for your study.
There is another blog on Mathematics for Data Science. It may help you to harmonize your study. Here is the link.
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