Last year I was awarded a Project TIER (Teaching Integrity in Empirical Research) fellowship, and last week my work on the fellowship wrapped up with a meeting with the project leads, other fellows from last year, as well as new fellows for the next year. In a nutshell Project TIER focuses on reproducibility. Here is a brief summary of the project’s focus from their website:
For a number of years, we have been developing a protocol for comprehensively documenting all the steps of data management and analysis that go into an empirical research paper.
Check out my guest post on the Simulation-based statistical inference blog:
Teaching computation as an argument for simulation-based inference
If you are interested in teaching simulation-based methods, or if you just want to find out more why others are, I highly recommend the posts on this blog. The page also hosts many other useful resources as well as information on upcoming workshops as well.
A few weeks ago I gave a two-hour Introduction to R workshop for the Master of Engineering Management students at Duke. The session was organized by the student-led Career Development and Alumni Relations committee within this program. The slides for the workshop can be found here and the source code is available on GitHub.
Why might this be of interest to you?
The materials can give you a sense of what’s feasible to teach in two hours to an audience that is not scared of programming but is new to R.
This post is about ggplot2 and dplyr packages, so let’s start with loading them:
library(ggplot2) library(dplyr) I can’t be the first person to make the following mistake:
ggplot(mtcars, aes(x = wt, y = mpg)) %>% geom_point() Can you spot the mistake in the code above? Look closely at the end of the first line.
The operator should be the + used in ggplot2 for layering, not the %>% operator used in dplyr for piping, like this:
The other day on the isostat mailing list Doug Andrews asked the following question:
Which R packages do you consider the most helpful and essential for undergrad stat ed? I ask in great part because it would help my local IT guru set up the way our network makes software available in our computer classrooms, but also just from curiosity. Doug asked for a top 10 list, and a few people have already chimed in with great suggestions.
Somehow almost an entire academic year went by without a blog post, I must have been busy… It’s time to get back in the saddle! (I’m using the classical definition of this idiom here, “doing something you stopped doing for a period of time”, not the urban dictionary definition, “when you are back to doing what you do best”, as I really don’t think writing blog posts are what I do best…)
I have gotten several requests for the R syntax I used to analyze the ranked-choice voting data and create the animated GIF. Rather than just posting the syntax, I thought I might write a detailed post describing the process.
Reading in the Data The data is available on the Twin Cities R User Group’s GitHub page. The file we are interested in is 2013-mayor-cvr.csv. Clicking this link gets you the “Display” version of the data.
