2023 Feedback on STATS 2020
dylanbeaudette opened this issue · comments
Dylan Beaudette commented
Ideas / commentary after working with mentees and reviewing lecture material.
- many namespace collisions → cut down on the number of packages used / loaded at any given time, this is esp. a problem with
library(tidyverse)
approach to loading everything aqp::allocate()
can be very noise, addverbose
argument- include examples / interpretation of
plot(Predict(model.rms))
andplot(summary(model.rms))
- explain / link to additional information on odds ratio, interpret all examples in the book
- label probability axes on all figures
- re-think / simplify glm examples: predictor variables too complex / hard to interpret
- more explanation of
rms::validate()
- CA790 regression examples need more context / explanation
- num. tax. examples: explain
type = 'n'
when making plots - link to / integrate evaluation of ordination, new exercise / examples
- tree methods: more expressive use of
corrplot()
→ colors, shading, ordering, etc. - ordered factor syntax / interpretation / importance
- convert everything to terra
- categorical data modeling, EDA, etc. → link to Michael Friendly's work