I read a really interesting post on Reddit explaining Markov Chain Monte Carlo, which drew the analogy between MCMC and a long game of Frogger.
I’ve been studying for another Maths exam. This time it’s the Open University M343 “Applications of Probability” course. It’s exam time so I’ve been making flash-cards to study with.
OK, here is an idea I had this morning: It’s called “Mnemonic Tagging”. The idea is that you create a list of keywords (or tags) that you use to mentally file mnemonic visualizations. For each of these tags you imagine something that represents the tag, followed by a chain of mnemonics that relate to that tag.
I have been studying maths for quite a few years now, but I still find it a struggle to remember various formulas/equations, especially when starting a new topic. I’ve been thinking about developing my own mnemonic system for math symbols to help me memorize equations easily.
I would need to relate various mathematical operators to something else that is easy to visualize. The bracketing of expressions is problematic, you would need to have a way of visualizing a collection of things that the operator acts on.
I think that having a mnemonic system for maths would help internalize the ideas and models within a domain. It’s obviously still a work in progress!
There’s a great article here on estimating correlations and means when you have missing data in your datasets. It uses the Expectation Maximisation algorithm to calculate the missing values, and what is interesting is how much the implied correlation changes after applying EM.
Garth Sundem of Geek Logik fame has a blog in which he comes up with formulas for wrapping every-day decisions in a mathematical framework. It’s something I’ve been thinking about for quite a while – especially with regards to procrastination. The trick is to quantify all the factors that you think are important in the issue you are considering, and then describe the relationship between the variables mathematically.