Resources
Find below a number of lists of useful resources covering research methods (in general) and specific to Computational Social Sciences and Cyberpsychology; programming in R; data science; media effects and other related areas.
Research Methods and Tools
Blogs
 The 20% Statistician  A blog on statistics, methods, and open science.
 Simply Statistics  a blog on data science, analysis, and statistics
Books
 Bit by Bit : Social Research in the Digital Age  Matthew Salganik (Open Book)
 Data Visualisation: A practical introduction  Kieran Healy (Open Book)
 Fundamentals of Data Visualisation: A primer on making informative and compelling figures  Claus Wilke (Open Book)
Useful Papers
Statistics Fundamentals
 Lakens, D. (2013). Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for ttests and ANOVAs. Frontiers in psychology, 4.
 Lakens, D., Scheel, A.M., Isager, P.M. (2018) Equivalence Testing for Psychological Research: A Tutorial. Advances in Methods and Practices in Psychological Science, 111.
 Greenland, S., Senn, S. J., Rothman, K. J., Carlin, J. B., Poole, C., Goodman, S. N., & Altman, D. G. (2016). Statistical tests, p values, confidence intervals, and power: a guide to misinterpretations. European journal of epidemiology, 31, 337–350.
 De Groot, A. D. (1956/2014). The meaning of “significance” for different types of research. Translated and annotated by EricJan Wagenmakers, Denny Borsboom, Josine Verhagen, Rogier Kievit, Marjan Bakker, Angelique Cramer, Dora Matzke, Don Mellenbergh, and Han L. J. van der Maas. Acta Psychologica, 148 , 188–194.
 Kass, R. E., Caffo, B. S., Davidian, M., Meng, X. L., Yu, B., & Reid, N. (2016). Ten Simple Rules for Effective Statistical Practice. PLOS Comput Biol, 12(6), e1004961.
Open Science
 Gilmore, R. O., Kennedy, J. L., & Adolph, K. E. (2018). Practical solutions for sharing data and materials from psychological research. Advances in Methods and Practices in Psychological Science, 1(1), 121130
 van’t Veer, A. E., & GinerSorolla, R. (2016). Preregistration in social psychology—A discussion and suggested template. Journal of Experimental Social Psychology, 67, 2 12.
Replication
Qualitative Methods and Reporting
 Guest, G., Namey, E., & McKenna, K. (2016). How Many Focus Groups Are Enough? Building an Evidence Base for Nonprobability Sample Sizes. Field Methods, 29(1).
 Twining, P., Heller, R. S., Nussbaum, M., & Tsai, C. C. (2017). Some guidance on conducting and reporting qualitative studies. Computers & Education, 106
Quantitative Methods and Reporting
Literature Synthesis and Reporting
General Research Methodology
Courses
MOOCs
Open Courses
R Programming Resources
First port of call: How do I…
 Top 50 ggplot2 Visualizations  50 ggplot2 examples with full code

The R Graph Gallery  A gallery of useful figures produced with R
 Hands on Programming with R  A good first resource for learning R fundamentals
 The Art of R Programming  It’s a good resource for systematically learning fundamentals such as types of objects, control statements, variable scope, classes and debugging in R.
 R Cookbook  A quick and simple introduction to conducting many common statistical tasks with R.
 Exploratory Data Analysis with R  Basic analytical skills for all sorts of data in R.
 R Programming for Data Science  More advanced data analysis that relies on R programming.
 Report Writing for Data Science in R  Rbased methods for reproducible research and report generation.
 R for Data Science  Free book from RStudio developers with emphasis on data science workflow.
 OpenIntro Statistics  A free online open introduction to statistics book
 The tidyverse style guide  a great how to on the tidyverse
 Answering Questions with data: Introductory statistics  open statistics textbook
 Learning Statistics with R  open statistics textbook (with datasets)
 An introduction to data cleaning with R  great overview on the processes of cleaning datasets with R
Interesting Blog Posts
If the list becomes unwieldy I’ll consider adding sections.
 A visual introduction to machine learning
 It’s the Effect Size, Stupid: What effect size is and why it is important
 Have smartphones really destroyed a generation? We don’t know
 5 years into academia – 45 things I’ve learned so far …
 SQL one of the most valuable skills
 Data science is different now
 Data Science Foundations: Know your data. Really, really, know it
 How the BBC Visual and Data Journalism team works with graphics in R
 Wikipedia Data Scraping with R: rvest in Action
 Open letter to journal editors: dynamite plots must die
 Reproducible Research in Computational Sciences
 What is statistical power? An illustration using simulated data
 The Two Friends Who Changed How We Think About How We Think