Big Update to Big Book of R (new look, new chapter, new books)

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29 June 2024

I’m super-excited to announce a bumper Big Book of R update.

Quarto update

Firstly, you’ll see that the site has been updated from bookdown to Quarto. Not only does it give us a nice visual update, the search function seems to work a lot better, and I think splitting the navigation into chapters on the left-hand side and content on the right makes this type of content easier to navigate.

Because the site is programmatically generated, I knew that porting it over wouldn’t necessarily be a simple matter, so I reached out Fathom Data (a Data Science consultancy with whom I’ve worked for many years) and they jumped at the opportunity to help out the R community. I want to give the biggest thanks to Fathom Data for porting the book over, debugging and even doing the update to the cover image. A special thanks to Bianca, Kalonji and Leani who worked on this project. They did so with minimal input from side and given my busy schedule, made sure basically everything happened asynchronously, making great use of detailed notes and screen recordings to keep me updated and get my input.

Fathom Data have written up a short blog post for some behind-the-scenes insight. If you ever need some DS work done (whether its data science itself, data engineering, architecture work, web scraping or even team training), I highly recommend them.

New chapter: Psychology

When there are enough books to warrant a chapter, I make one. In this case, the new chapter is Psychology and it’s already got 7 entries!

7 new books

And now onto the addition of new books. Enjoy!

Principles of Psychological Assessment: With Applied Examples in R

This book highlights the principles of psychological assessment to help researchers and clinicians better develop, evaluate, administer, score, integrate, and interpret psychological assessments. It discusses psychometrics (reliability and validity), the assessment of various psychological domains (behavior, personality, intellectual functioning), various measurement methods (e.g., questionnaires, observations, interviews, biopsychological assessments, performance-based assessments), and emerging analytical frameworks to evaluate and improve assessment including: generalizability theory, structural equation modeling, item response theory, and signal detection theory. The text also discusses ethics, test bias, and cultural and individual diversity. The book provides practical data and analysis examples in R to help people better understand principles of psychological assessment and how to apply them. The book uses the freely available petersenlab package for R.

R Programming for Actuarial Science

Professional resource providing an introduction to R coding for actuarial and financial mathematics applications, with real-life examples

R Programming for Actuarial Science provides a grounding in R programming applied to the mathematical and statistical methods that are of relevance for actuarial work.

R for Social Network Analysis

The goal of the book is to gather the most important topics in SNA in one place. “Important” is of course very subjective and it is not clear how to draw the line of what should be included and what not. We will start with the low hanging fruits, meaning repurposing our own material. That is, material from our workshops and courses (for instance what is already available here). This should cover the most generally relevant topics in SNA. Everything beyond that will be added over time as we (or the community!) deems necessary.

Customer Intelligence with R

Customer Intelligence with R’ (CI with R) is for learning the basic application of customer activation, development, retention, and segmentation (CADRS) with R. It is aimed to be educational outside of the academia.

Applied Machine Learning for Tabular Data

We want to create a practical guide to developing quality predictive models from tabular data. We’ll publish materials here as we create them and welcome community contributions in the form of discussions, suggestions, and edits. The book takes a holistic view of the predictive modeling process and focuses on a few areas that are usually left out of similar works. For example, the effectiveness of the model can be driven by how the predictors are represented. Because of this, we tightly couple feature engineering methods with machine learning models. Also, quite a lot of work happens after we have determined our best model and created the final fit. These post-modeling activities are an important part of the model development process and will be described in detail.

Programación práctica con R

Este es el sitio web para la versión en español de “Hands-On Programming with R” (en lo adelante “Programación Práctica con R”) de Garrett Grolemund. Este libro le enseñará cómo programar en R, con ejemplos prácticos. Fue escrito para personas que no son programadores con el objetivo de proporcionar una introducción amigable al lenguaje R. Aprenderá a cargar datos, ensamblar y desensamblar objetos de datos, navegar por el sistema de entorno de R, escribir sus propias funciones y utilizar todas las herramientas de programación de R. A lo largo del libro, utilizará sus nuevas habilidades para resolver problemas prácticos de ciencia de datos.

R para principiantes

R para principiantes pretende ser un materal introductorio al lenguaje de programación R, dirigído a personas que nunca han usado R o ningún otro lenguaje de programación, ni tiene conocimiento previo de probabilidad y estadística.

Este libro tiene como propósito que adquieras los fundamentos del uso de R como un lenguaje de programación, desde sus conceptos más elementales, hasta la definición de funciones y generación de gráficos.

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The post Big Update to Big Book of R (new look, new chapter, new books) appeared first on Oscar Baruffa.

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