Hey everyone,
Studying is going alright, but it looks like it’s taking over all my other activities so I won’t really have any creative projects to write about until the end of next month. I’ve managed to stay in shape so far, and by pure coincidence, I ran into one of my former UT teammates, Stephen, during a training ride at Memorial Park. He’s moved down here for the long term, which is pretty cool given that Ken and I are in the same general location. In the meantime, I’ve planned some projects in the back of my mind that I might want to start as soon as I finish my exam:
1. Monty Hall Simulation
2. N-Back
3. Project Euler
4. .GPX and .TCX data extraction
The first project, The Monty Hall Problem, involves a game-show situation in which a contestant chooses one of three objects, each hidden behind a curtain. Two of the objects are something undesirable, like a goat, and the other object is something desirable, like a fancy sports car. The hostess reveals one of the goats and asks the contestant if they wish to change their mind. It turns out the answer is the player should switch, which seems counterintuitive upon first exposure since most people would erroneously assume that there’s still 50/50 chance of getting a fancy sports car regardless of choice. The general proof of the problem involves Bayesian Statistics. I’d like to do a simple VBA simulation of this scenario to see how it works empirically, and perhaps in this way I can gain an intuitive understanding of how this new knowledge affects the conditional probability.
For the second project, I’d like to reconstruct a game called N-Back using VBA as a prototype, and then wxPython for the final version. N-Back is an iterative game in which the player must recognize patterns from say, 1,2,…,n iterations ago. It’s a game that tests the working memory of the player. I think this would be a very good exercise for GUI programming.
One of my friends recommended that I give Project Euler a try. It’s a website that has a bunch of problems that you can solve efficiently by constructing algorithms. I heard that attempting to recreate solutions in different programming languages is a good way learn new languages.
The fourth project involves the .GPX and .TCX data files that contain the training data I pull from my Garmin. It’s possible to convert them into tables that you can import in to R for statistical analysis. The plotting features of the free Garmin Training Center software are very limited, so I’d like to create a platform using R to make it easier to slice and compare two different data sets.
Other than that, I’ve been given some neat projects at work where I’ll be able to take a look at some huge data sets using SQL Server. I’ve also signed up for a meeting with the Houston-R users group on Wednesday, at which we’ll discuss the use of R in predictive modeling competitions.