1) How-to’s & long-form tutorials
Most tutorials use R (RStudio/OSX), occasionally I will post on Stata and/or Git.
- The UFC brings out the big guns (again…) post and on Github.
- Exploratory Data Analysis or check this post out on Github or my listed post.
- Scraping wikipedia tables or see the github repo
- How to explore and manipulate a dataset from the fivethirtyeight package in R. UPDATE: fixed a few lines on the barplot and created a new repo
- Storybench Tutorials – these are tutorials I’ve written for Storybench.org
- Tidyverse/RStudio demonstration for Quesgen
- Wrangle multiple .csv files with a function in R or the blog post
- Reproducible Research In Plos Tutorials
2) Projects I’m working on
These are projects I’m doing for work (or pleasure). They range from Github repos, manuscript drafts, or tools/tips that I’ve found helpful. A Shiny app I’m building for the Diabetes Technology Society:
3) Blog posts and articles worth looking at
These are posts and articles I’ve found helpful or interesting. The topics range from exercise science, statistical methods, data science/programming, or basic news articles.
- The Temin Effect – Editorial from David Epstein & Malcolm Gladwell & original research from Gurwin et al.
- Winner’s Curse? – great article on the field of machine learning/big data methods.
…”seemingly fast progress was perhaps slower than it could have been if the field had enforced higher levels of empirical rigor.”
Meritocracy or social justice?
In closing, we wish to emphasize that we are not advocating meritocracy; these issues are more a matter of values than science. At first glance meritocracy seems unquestionably good, but it could have unintended consequences such as creating social inequalities if societal rewards such as wealth are doled out on the basis of genetically driven abilities.*
- How the odds ratio confounds: a brief study in a few colorful figures – awesome post on odds ratios vs. relative risks
- A great curated list of journalism with R resources.
- Two excellent wrangling and visualization resources:
- Up and running with blogdown – a great blog post by Alison Presmanes Hill.
- Text Mining with R
- Modern Data Science in R
- Unforgivable Blackness: The Rise and Fall of Jack Johnson
- Causal Inference in Statistics: A Primer
Posts from this category:
- ggplot2 – Elegant Graphics for Data Analysis by Hadley Wickham. It’s the only text from HW that isn’t also free online (see R for Data Science, Advanced R-2nd Ed, R packages, and the new Tidyverse Style Guide), and it’s worth every penny.
- Doing Data Science – Straight Talk from the Frontline by Cathy O’Neil and Rachel Schutt. Full of awesome thought experiments and accessible information.
- The Sense of Style: The Thinking Person’s Guide to Writing in the 21st Century by Steven Pinker. Everything Pinker writes is pretty much golden–I can’t recommend him enough.