25 Field specific

25.1 Analyzing Financial and Economic Data with R

Marcelo S. Perlin

Not surprisingly, fields with abundant access to data and practical applications, such as economics and finance, it is expected that a graduate student or a data analyst has learned at least one programming language that allows him/her to do his work efficiently. Learning how to program is becoming a requisite for the job market.

https://www.msperlin.com/afedR/

25.2 Data Science in Education Using R

Ryan A. Estrellado, Emily A. Bovee, Jesse Mostipak, Joshua M. Rosenberg, and Isabella C. Velásquez

Dear Data Scientists, Educators, and Data Scientists who are Educators:

This book is a warm welcome and an invitation. If you’re a data scientist in education or an educator in data science, your role isn’t exactly straightforward. This book is our contribution to a growing movement to merge the paths of data analysis and education. We wrote this book to make your first step on that path a little clearer and a little less scary.

https://datascienceineducation.com/

25.3 The Plain Person’s Guide to Plain Text Social Science

Kieran Healy

As a beginning graduate student in the social sciences, what sort of software should you use to do your work?1 More importantly, what principles should guide your choices? I offer some general considerations and specific answers.

https://plain-text.co/index.html#introduction

25.4 Technical Foundations of Informatics

Michael Freeman and Joel Ross

This book covers the foundation skills necessary to start writing computer programs to work with data using modern and reproducible techniques. It requires no technical background. These materials were developed for the INFO 201: Technical Foundations of Informatics course taught at the University of Washington Information School; however they have been structured to be an online resource for anyone hoping to learn to work with information using programmatic approaches.

https://info201.github.io/

25.5 Practical R for Mass Communication and Journalism

Sharon Machlis

Welcome to this excerpt from Practical R for Mass Communication and Journalism. In these sample chapters, you’ll:

learn how to find your way around R and RStudio, see how much you can do in just a few lines of code, start doing some basic data exploration, and get some ideas and sample code for using R in analyzing election results. I hope you find this excerpt useful! If you do and would like to read more, you can order the complete book from CRC Press or Amazon.

Free samples. Full paid product ~ $55 http://www.machlis.com/R4Journalists/index.html

25.6 An introduction to quantitative analysis of political data in R

Erik Gahner Larsen & Zoltán Fazekas

In this book, we aim to provide an easily accessible introduction to R for the collection, study and presentation of different types of political data. Specifically, the book will teach you how to get different types of political data into R and manipulate, analyze and visualize the output. In doing this, we will not only teach you how to get existing data into R, but also how to collect your own data.

http://qpolr.com/

25.7 Machine Learning for Factor Investing

Guillaume Coqueret and Tony Guida

This book is intended to cover some advanced modelling techniques applied to equity investment strategies that are built on firm characteristics.

http://www.mlfactor.com/

25.8 Introduction to Econometrics with R

Christoph Hanck, Martin Arnold, Alexander Gerber, and Martin Schmelzer

Instead of confronting students with pure coding exercises and complementary classic literature like the book by Venables & Smith (2010), we figured it would be better to provide interactive learning material that blends R code with the contents of the well-received textbook Introduction to Econometrics by Stock & Watson (2015) which serves as a basis for the lecture.

https://www.econometrics-with-r.org/

25.9 How to be a modern scientist

Jeffrey Leek

A book about how to be a scientist the modern, open-source way. The face of academia is changing. It is no longer sufficient to just publish or perish. We are now in an era where Twitter, Github, Figshare, and Alt Metrics are regular parts of the scientific workflow. Here I give high level advice about which tools to use, how to use them, and what to look out for. This book is appropriate for scientists at all levels who want to stay on top of the current technological developments affecting modern scientific careers.

Pay what you want for the ebook, minimum $0.00

https://leanpub.com/modernscientist