If your data is just 1’s and 0’s, it can be difficult to visualize alongside a best-fit line from a logistic regression.
Even with transparency, the overplotted data points just turn into a smear on the top and bottom of your plot, adding little information.
If you’ve ever tried to look “under the hood” of an R function, you know that sometimes it can be tricky to figure out what’s going on, especially if you use R more as a statistical tool than as a programming language.
A wide range of chemical information is freely available online, including identifiers, experimental and predicted chemical properties. However, these data are scattered over various data sources and not easily accessible to researchers. Manual …
In March (which feels like years ago, now), when Universities started seriously thinking about their response to COVID-19, I was teaching Ecological Models and Data as instructor of record and finishing my dissertation up.
I’m currently teaching Ecological Statistics and Data, a class I inherited from Lee Brown and Elizabeth Crone. In a lecture on population dynamics, they do some really cool things with generalized linear model—things that I don’t think are standard practice and as far as I can tell from googling, aren’t well documented.
I woke up this morning to an email saying my first R package, holodeck, was on it’s way to CRAN! It’s a humble package, providing a framework for quickly slapping together test data with different degrees of correlation between variables and differentiation among levels of a categorical variable.
This was my first time attending RStudio::conf, and I went primarily to explore my career options in data science. I mainly stuck to teaching and modeling related talks since that’s how I already use R.
Plants often experience multiple sources of stress simultaneously, yet little is known about interactive effects of multiple stressors on plant metabolic responses. Plants are well known to respond to both drought and insect herbivory through the …