I have written a few posts discussing descriptive analyses of evaluation of National Standards for New Zealand primary schools.The data for roughly half of the schools was made available by the media, but the full version of the dataset is … Continue reading → [Read more...]

Eric and I have been exchanging emails about potential analyses for the school data and he published a first draft model in Offsetting Behaviour. I have kept on doing mostly data exploration while we get a definitive full dataset, and … Continue reading → [Read more...]

I like the idea of having data on school performance, not to directly rank schools—hard, to say the least, at this stage—but because we can start having a look at the factors influencing test results. I imagine the opportunity in … Continue reading → [Read more...]

Oddities tend to jump out when one uses software in a daily basis. The situation is even clearer when using software for teaching: many more people looking at it with fresh eyes. Let’s say that we are fitting a simple … Continue reading → [Read more...]

This is one of those times of the year: struggling to keep the head above the water, roughly one month before the last lecture of the semester. On top trying to squeeze trips, meetings and presentations in between while dealing … Continue reading → [Read more...]

Suicide is a tragic and complex problem. This week New Zealand’s Chief Coroner released its annual statistics on suicide, which come with several tables and figures. One of those figures refers to monthly suicides in the Christchurch region (where I … Continue reading → [Read more...]

Today Scott Chamberlain tweeted asking for a better/faster solution to building an m x n matrix with randomly assigned 0/1. He already had a working version: Now, I’m the first to acknowledge that I’ve never got the ‘apply’ family of … Continue reading → [Read more...]

Reached mid-semester point, with quite a few new lectures to prepare. Nothing extremely complicated but, as always, the tricky part is finding a way to make it meaningful and memorable. Sometimes, and this is one of those times, I sound … Continue reading → [Read more...]

INLA is not the Norwegian answer to ABBA; that would probably be a-ha. INLA is the answer to ‘Why do I have enough time to cook a three-course meal while running MCMC analyses?”. Integrated Nested Laplace Approximations (INLA) is based … Continue reading → [Read more...]

When running stats labs I like to allocate a slightly different subset of data to each student, which acts as an incentive for people to do their own work (rather than copying the same results from a fellow student). We … Continue reading → [Read more...]

Back teaching a couple of subjects and it’s the constant challenge to find enough common ground with students so one can push/pull them to the other side of new concepts. We are not talking about complex hierarchical models using mixed … Continue reading → [Read more...]

Disappeared for a while collecting frequent flyer points. In the process I ‘discovered’ that I live in the middle of nowhere, as it took me 36 hours to reach my conference destination (Estoril, Portugal) through Christchurch, Sydney, Bangkok, Dubai, Madrid … Continue reading → [Read more...]

I like statistics and I struggle with statistics. Often times I get frustrated when I don’t understand and I really struggled to make sense of Krushke’s Bayesian analysis of a split-plot, particularly because ‘it didn’t look like’ a split-plot to … Continue reading → [Read more...]

Forestry is the province of variability. From a spatial point of view this variability ranges from within-tree variation (e.g. modeling wood properties) to billions of trees growing in millions of hectares (e.g. forest inventory). From a temporal point of view … Continue reading → [Read more...]

The end is near! At least the semester is coming to an end, so students have crazy expectations like getting marks back for assignments, and administrators want to see exam scripts. Sigh! What has been happening meanwhile in Quantum Forest? … Continue reading → [Read more...]

Some people will say ‘you have to learn R if you want to get a job doing statistics/data science’. I say bullshit, you have to learn statistics and learn to work in a variety of languages if you want to … Continue reading → [Read more...]

A while ago I wanted to run a quantitative genetic analysis where the performance of genotypes in each site was considered as a different trait. If you think about it, with 70 sites and thousands of genotypes one is trying … Continue reading → [Read more...]

I’m a bit obsessive with words. May be I should have used learning in the title, rather than teaching code. Or perhaps remembering code. You know? Code where one actually has very clear idea of what is going on; for … Continue reading → [Read more...]

It has been month and a half since I compiled a list of statistical/programming internet flotsam and jetsam. Via Lambda The Ultimate: Evaluating the Design of the R Language: Objects and Functions For Data Analysis (PDF). A very detailed evaluation … Continue reading → [Read more...]

— “You are a pussy” emailed my friend. — “Sensu cat?” I replied. — “No. Sensu chicken” blurbed my now ex-friend. What was this about? He read my post on R, Julia and the shiny new thing, which prompted him … Continue reading → [Read more...]