17 Statistics

17.1 Common statistical tests are linear models: a work through

Steve Doogue

This is a reworking of the book Common statistical tests are linear models (or: how to teach stats), written by Jonas Lindeløv. The book beautifully demonstrates how many common statistical tests (such as the t-test, ANOVA and chi-squared) are special cases of the linear model. The book also demonstrates that many non-parametric tests, which are needed when certain test assumptions do not hold, can be approximated by linear models using the rank of values.

https://steverxd.github.io/Stat_tests/

17.2 Learning statistics with R: A tutorial for psychology students and other beginners. (Version 0.6.1)

Danielle Navarro

Learning Statistics with R covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software. The book discusses how to get started in R as well as giving an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book.

The book is free online.

https://learningstatisticswithr-bookdown.netlify.app/

17.3 Answering questions with data

Matthew J. Crump

This is a free textbook teaching introductory statistics for undergraduates in Psychology. This textbook is part of a larger OER course package for teaching undergraduate statistics in Psychology, including this textbook, a lab manual, and a course website.

Looks like a comprehensive stats resource!

https://crumplab.github.io/statistics/

17.4 Forecasting: Principles and Practice

Rob J Hyndman and George Athanasopoulos

This textbook is intended to provide a comprehensive introduction to forecasting methods and to present enough information about each method for readers to be able to use them sensibly.

The book is written for three audiences: (1) people finding themselves doing forecasting in business when they may not have had any formal training in the area; (2) undergraduate students studying business; (3) MBA students doing a forecasting elective.

https://otexts.com/fpp2/

17.5 An Introduction to Statistical and Data Sciences via R

Chester Ismay and Albert Kim

An incredibly beginner friendly introduction to both datascience and statistics concepts as well as R.

The book is free to read online.

https://moderndive.com/

17.6 Statistical Rethinking

A Bayesian Course with Examples in R and Stan

Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds your knowledge of and confidence in making inferences from data. Reflecting the need for scripting in today’s model-based statistics, the book pushes you to perform step-by-step calculations that are usually automated. This unique computational approach ensures that you understand enough of the details to make reasonable choices and interpretations in your own modeling work.

https://xcelab.net/rm/statistical-rethinking/

17.7 OpenIntro Statistics

David Diez, Mine Cetinkaya-Rundel, Christopher Barr, and OpenIntro.

A complete foundation for Statistics, also serving as a foundation for Data Science.

Leanpub revenue supports OpenIntro (US-based nonprofit) so we can provide free desk copies to teachers interested in using OpenIntro Statistics in the classroom and expand the project to support free textbooks in other subjects.

More resources: openintro.org.

Pay what you want for the ebook, minimum $0.00, however if you are able to, please consider the cause above. Thanks!

https://leanpub.com/openintro-statistics

17.8 Statistical inference for data science

Brian Caffo

This book gives a brief, but rigorous, treatment of statistical inference intended for practicing Data Scientists.

Pay what you want for the ebook, minimum $0.00

https://leanpub.com/LittleInferenceBook

17.9 Statistics (The Easier Way) With R, 3rd. Ed. (TIDYVERSION)

Nicole Radziwill

This introductory applied statistics handbook shows you how to run tests analytically, and then how to run exactly the same steps using R. No steps are skipped, making this particularly well suited for beginners or people who need a quick lookup. Used at 30+ universities around the globe.

https://amzn.to/3b9ha8s - varies between $37-43 & you can request free PDF after your order https://www.e-junkie.com/ecom/gb.php?&c=single&cl=147256&i=1614407 - $25 for PDF only

17.10 End-to-End Solved Problems With R: a catalog of 26 examples using statistical inference

Nicole Radziwill

Lots of worked problems, analytically and in R! Useful supplement for an introductory applied stats class.

https://amzn.to/2EREAn2 - used for $4-18, new $19-20 https://www.e-junkie.com/ecom/gb.php?c=single&cl=147256&i=1548704 - $10 for PDF only

17.11 Bayes rules!

The primary goal of Bayes Rules! is to make modern Bayesian thinking, modeling, and computing accessible to a broad audience. Bayes Rules! empowers readers to weave Bayesian approaches into an everyday modern practice of statistics and data science.
The overall spirit is very applied: the book utilizes modern computing resources and a reproducible pipeline; the discussion emphasizes conceptual understanding; the material is motivated by data-driven inquiry; and the delivery blends traditional “content” with “activity”.

Free online book under construction but with 5 complete chapters on 2020/10/15

https://www.bayesrulesbook.com/