R

What HoPTM looks like from the inside

As mentioned some days ago our Handbook of Process Tracing Methods is out in the wild … Here is a bit of an overview of what is going on inside :)

Pictures

So, here we go - new blogdown site … thanks to Dan (https://twitter.com/dsquintana) to kicked me over the edge actually doing this … Things are fine, the site is up - pictures are still linked back to my old wordpress site … will figure this out eventually … but this is live now - for your reading pleasure :)

BernR Meetup

Today (Dec 10th 2018) we will meet for the first BernR Meetup (https://www.meetup.com/Bern-R/) – hope to learn new things and get to know cool R people. More to follow soon .

Something about reverse inference

Often, when we run process tracing studies (e.g., eye-tracking, mouse-tracking, thinking-aloud) we talk about cognitive processes (things we can’t observe) in a way that they are actually and directly observable.

Eye-Tracking with N > 1

This is one of the fastest papers I have ever written. It was a great collaboration with Tomás Lejarraga from the Universitat de les Illes Balears. Why was it great? Because it is one of the rare cases (at least in my academic life) where all people involved in a project contribute equally and quickly.

Before R there was S

Before there was R, there was S. R was modeled on a language developed at AT&T Bell Labs starting in 1976 by Rick Becker and John Chambers (and, later, Alan Wilks) along with Doug Dunn, Jean McRae, and Judy Schilling.

The exams package

I gave the R package exams a shot for my decision making lecture. Here is what it does: “Automatic generation of exams based on exercises in Sweave (R/LaTeX) or R/Markdown format, including multiple-choice questions and arithmetic problems.

all that mutate() and summarise() beauty

The friendly people from RStudio recently started a webinar series with talks on the following topics (among others): Data wrangling with R and RStudio The Grammar and Graphics of Data Science (both dplyr happiness)

dplyr is growing up …

dplyr is the new plyr – and it is awesome! fast, consistent and easy to read … check out a set of instructional pages, presentation and videos here

*apply in all its variations …

Here is an excellent stackoverflow post on how *apply in all its variations can be used. One of the followups points at plyr (from demi-R-god Hadley Wickham) which provides a consistent naming convention for all the *apply variations.