ARC Discovery Projects have been returned to their authors, and we are putting our responses together for the rejoinders. Interesting to see that we got a comment suggesting that we use the less restrictive CC-by instead of CC-by-nc-sa as we’d suggested. We weren’t successful in our Linkage Project applications, which is disappointing as they were interesting projects (well, we thought so). Continuing to bring research funding in is an ongoing struggle for all research groups and I feel it’s only going to get harder as the new federal government’s research priorities appear to be more aligned to medical science that delivers treatments than to our group’s traditional strengths.

SEB113 is pretty much completely over for the semester, with marks having been entered for almost every student. Overall I think the students did fairly well. We had some issues with the timetable this semester. Ideally, we’d like the Lecture, then all of the computer labs, then all of the workshops, so that we can introduce a statistical idea, show the code and then apply the idea and code in a group setting. Next semester, we have the lecture followed immediately by the workshops with the computer labs dotted throughout the remainder of the week. This has provided us with an opportunity to try some semi-flipped classroom ideas, where students are able/expected to do the computer lab at home at their own pace rather than watch a tutor explain it one line at a time at the front of a computer lab.

I’m teaching part of a two day course on the use of R in air pollution epidemiology. My part will introduce Bayesian statistics with a brief overview, a discussion about prior distributions as a means of encoding *a priori* beliefs about model parameters, and discuss the use of Bayesian hierarchical modelling (as opposed to more traditional ANOVA techniques) as a way of making the most of the data that’s been collected. The other two presenters are Dr Peter Baker and Dr Yuming Guo. The course is being run by the CAR-CRE, who partially fund my postdoctoral fellowship.

I had meant to post this back when they were doing the rounds, but there’s a bunch of plots that attempt to show that correlation isn’t causation and that spurious correlations exist in large data sets. Tom Christie has responded to this by going over the fact that correlation in time series isn’t as simple as in the case of independent, identically distributed data. One should be careful that one’s criticism of bad statistics is itself founded on good statistics.