Welcome to the latest edition of Big Book of R updates. We’re now at nearly 400 books in the collection of free (and some paid) titles!
In this update, I’ve added a new People Analytics chapter that gathers the growing list of titles dedicated to the use of R in Human Resources.
And now – onto the new books!
by Martin Frigaard
This book is a resource to help ‘connect the dots’ between building scalable Shiny applications and writing R packages. Adopting R package development practices in the early stages of your Shiny app will improve the reusability, maintainability, and shareability of all your hard work.
R for HR: An Introduction to Human Resource Analytics Using R
by David E. Caughlin
The foundation of HR analytics formed over a century ago with the emergence of disciplines like industrial and organizational (I/O) psychology. In recent decades, advances in information technology and systems have reduced the time HR professionals spend on transactional and administrative activities, thereby creating more time and opportunity for transformational activities supporting the realization of strategic organizational objectives. HR analytics has the potential to play an integral role in such transformational activities, as it can inform HR system design
The Hitchhiker’s Guide to Linear Models
This book aims to get straight to the point, and the only thing I assume here is that you have used spreadsheets at some point and that you are motivated to estimate linear models in R. Here I do not assume that you know how to install R or the basics of the R programming language.
Applied Demographic Data Analysis
by Corey S. Sparks, PhD
My goal for this book is to take the lessons I’ve learned teaching statistics to a diverse and often cursorily trained group of students who have problems they care about, that they need to bring demographic data to bear upon. This is a challenge, and I have always been a stalwart proponent of teaching statistics and data analysis in a very applied manner. As such, this book won’t be going into rigorous proofs of estimators or devoting pages to expositions of icky algebra; instead it will focus on exploring modern methods of data analysis that in used by demographers every day, but not always taught in our training programs.
Introduction to NFL Analytics with R
by Bradley J. Congelio
This is the best resource an aspiring data scientist looking to work with football data can use. It has something for all levels, including data analysis, visualization, advanced modeling, and more. The code and the insights in Introduction to NFL Analytics with R are invaluable and can help everyone from beginners to those who have worked with data for years.
That’s it for this release – enjoy!
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