what’s this blog about in 2018?

More Bayes, more how-to, fewer posts per month


what happened to dataviz of the week?

It’s over; there are no more weeks. Hand of God has struck the hour, no more pie charts have the power, etc etc. It became a staple of the blog through 2017 but I don’t know if it is really useful to anyone. There are many places where you can hear about new, funky viz; I suggest Twitter + Feedly. It started on my noticeboard when I was a lecturer. Some viz was good and some was bad. I just stuck it up each week without explanation. My colleagues often mis-classified them to good/bad, which was interesting in itself. On the blog, some critique is needed, but (see below), I can’t do so much of that any more.

I think it would be more useful to people to have posts about how to achieve X dataviz goal (where X is not an element of R-bloggers), and thinking about dataviz, weighing up options etc.

You can expect more building from basic components, including R base graphics, SVG and D3. There are no free lunches.

Of course, I have a book in the pipeline, which contains some overarching thoughts on making and critiquing dataviz, and those will get reflected here over the spring and summer.



I did a little Twitter poll asking what people wanted to hear about from @robertstats, and it was Bayes that came out in front. I was quite surprised by that, but I’m happy to oblige. I won’t try to compete with in-depth technical blogs like Christian Robert’s. The popularity of how-to posts makes me think that I should apply that here. So, there will be approachable posts for people who have passed the absolute beginner stage but are still fumbling through the foothills; I think that’s a gap in the proverbial market.

Expect Stan to feature heavily, plus latent variables and various forms of uncertainty arising from biases and imperfect data.


You might notice that, naked of the university indemnity and legal precedent of academic freedom, I don’t cuss people nearly as much as I used to, and that’s not going to change. I have a kid to feed, you know.


philosophy of science

I don’t have much left to say about this, but I think a Platonic style dialogue where some ultra-frequentist gets made to look stupid could be a useful way of showcasing the various reasons why Bayes wins.

I also have notes on “Aboutness” by Stephen Yablo to share with you.



The main thrust of my freelance activity is training and coaching, and I’ll talk a bit here about what makes for good learning and teaching in data science / statistics / machine learning. Like Colonel Saunders, I won’t tell you all my secrets, but I might lure you in by revealing that there are some. And if you are a teacher you will probably recognise what I’m getting at.

The coaching front might feature some thoughts on building a career and an identity in this data science age. If you’re a millennial and work in tech, I feel sorry for you, son. But you don’t have to work yourself to an early grave. My homeboy Henry Thoreau might turn up here, or he might not.



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