Hi there Reader,

There’s been a sudden jump in RStats peeps joining BlueSky, and some very familiar faces from the twitter days. You can find me here, and there’s a very handy “starter pack” which is a list of accounts to jumpstart your feed with!

We’ve got a bumper edition in this latest update of Big Book of R. 10 new books in total. Many thanks to Peter Kemp, Isabella Velásquez, David Díaz Rodríguez and the ever-mysterious “Gary” for their contributions.

Firstly, we have 4 new books added to the Spanish chapter i.e. Modelado Ordenado con R, Paquetes de R, R Avanzado and R para la Ciencia de Datos 2nda edición.

and there’s 6 new additions in English:

Fantasy Football Analytics: Statistics, Prediction, and Empiricism Using R

• Isaac T. Petersen

This book is about learning statistics, prediction, and empiricism through the lens of fantasy football. It teaches readers how to use the free software R to perform fantasy football data analysis.

​https://www.bigbookofr.com/chapters/sport%20analytics#fantasy-football-analytics-statistics-prediction-and-empiricism-using-r​

​

End To End Data Science With R

• Rene Essomba

Great introduction to R, covering a wide range of topics. Covers exploratory data analysis, visualization, supervised learning, unsupervised learning, time-series, NLP, and image classification.

​https://www.bigbookofr.com/chapters/data%20science#end-to-end-data-science-with-r​

​

Quantitative methods in the context of education research

• ​Peter EJ Kemp​
• ​Richard Brock​
• ​Amy O’Brien​
• Carla Finesilver
• Lulu Healy
• ​David Pepper​

This book takes the reader through the process of learning the R statistical programming language through the analysis of the 2022 PISA survey data.

​https://www.bigbookofr.com/chapters/field%20specific#quantitative-methods-in-the-context-of-education-research​

​

An Introduction to Bayesian Data Analysis for Cognitive Science

• ​Bruno Nicenboim​
• ​Daniel Schad​
• ​Shravan Vasishth​

Bayesian data analysis and cognitive modeling using the probabilistic programming language Stan, and the front-end to Stan called brms.

​https://www.bigbookofr.com/chapters/statistics#an-introduction-to-bayesian-data-analysis-for-cognitive-science​

​

The Data Preparation Journey: Finding Your Way With R

• Martin Monkman

The book will introduce the principles of data preparation, framed in a systematic approach that follows a typical data science or statistical workflow. With that context, readers will then work through practical solutions to resolving problems in data using the statistical and data science programming language R. These solutions will include examples of complex real-world data.

​https://www.bigbookofr.com/chapters/getting%20cleaning%20and%20wrangling%20data#the-data-preparation-journey-finding-your-way-with-r​

​

A crash course on urban accessibility with R

• Rafael H. M. Pereira

Routing and accessibility analyses are increasingly used in urban and transport research and planning. In this workshop, you will learn how to estimate travel time matrices and perform accessibility analyzes in multimodal transport networks using the {r5r} and {accessibility} packages in the R programming language.

The workshop will also illustrate how to calculate different measures of inequality of access to opportunities and accessibility poverty, which are crucial to assess the accessibility impacts of transportation projects from a transportation equity perspective.

​https://www.bigbookofr.com/chapters/geospatial#a-crash-course-on-urban-accessibility-with-r​

​

Thanks for reading, and I hope you have a great week!

Oscar