Awareness of students’ mental health is growing in academia right now. Unsurprisingly, faculty suffer mental illness too, and many do not seek help from their institutions. The fear that disclosure, even to the disability office, will have negative effects on one’s professional career is a common reason for not seeking help.
In 2016 I started thinking about using sum to zero contrasts and wrote a brief blog post about them. Someone read it! I got this email the other day: Thank you for this post. I have difficulties understanding it though because the text below the first R output seems not to match with the model output. At first, one cannot see which species is species1,2 etc. Second the numbers are also not correct… Would be cool if you could check it and correct it because then it would be a useful post!
I set up 4 10 gallon aquaria in the teaching lab this semester. The goal was to observe the nitrogen cycle as the tanks settled in. I also needed an excuse to try out the new Hach environmental water testing kit that we ordered. The data are on figshare.
A colleague wrote: Hi Drew, I’m trying to make a really simple (I think) plot in R, but am not sure how to do it. I want to make the attached, where the size of each “bubble” in each grid location depends on a single raw data point (% cover of a type of grass). Can you point me in the right direction? This is the goal.
Really. I have no concept of what my students’ lives are like, and this is something I have to constantly remind myself. I cannot make assumptions about their situations based on my own experience.
I’ve been teaching students
ggplot2 for graphics exclusively for a year or more now. One issue that seems to throw students is the specification of different data sets for some layers. Part of the confusion seems to arise from reversing the order of arguments between
geom_*(). I’m trying to combat this by always naming my arguments. Is this a good idea?
So I’ve kicked the ball on migrating to blogdown/hugo/netlify!
This is a shorter summary that will hopefully be used by Hugo.
Brian Cade published a scathing condemnation of current statistical practices in ecology. It promises to be highly influential; I have seen it cited by reviewers already. I agree with a great many points Brian raised. I also disagree with one very central point.
The semester long course from Data Carpentry uses
read.csv(..., sep=' ') to read tab delimited files. I’ve been using
readr::read_tsv() because … well, just because! A student in my data management class (reasonably) had this question: Will both of these essentially do the same thing or are there considerations for using one vs. the other?