For this project, I decided to look at giving data from around the world. I find most fascinating the psychology and sociology behind charity, but I can only infer on that given that I don’t have the means to test various ideas. Most numbers given by organizations are dispersed among many sites making it hard to collect. But, luckily, Gallup conducts a survey that provides some numbers so we can entertain such a discussion.
I just turned in Assignment 2 for my Data Analysis Course so I can now share it on
here (Unfortunately, I’ve been warned that people have been plagiarizing so I’ve removed my files to prevent cheating… which ironically I did not list as a challenge for a MOOC below, but should be added). In this assignment, we were given sensor data from the Samsung Galaxy SII recorded while users performed specific activities. The goal was to develop a model on some training data to predict what activity the test subjects are performing. As usual, I wish I had more time to spend on it because I always feel like there is more I can add. Using random forests, I got a misclassification error rate of about 5% on the test subjects. Not too shabby, but at some point I would like to compare it to other models such as SVMs or Neural networks. Continue reading
47 years. That is the life expectancy of Sierra Leone, the lowest of all countries. Compare that with the highest life expectancy of 83 years in San Marino. Its easy to brush these numbers aside as another dull statistic, but that is a 36 year difference. I have yet to even experience that length of time! Imagine being told, that your life will end 36 years earlier than expected. It’s not very easy for most of us to comprehend. Continue reading
I thought I’d share my first assignment from the Coursera class, Data Analysis. It’s a very simple analysis, but it did get me back into the feel of writing research papers (as opposed to the terse sentence fragments I email at work). I’m posting it here to demonstrate what level of work you can expect from such a course… and because charts in R blow Excel out of the water. Continue reading
A week or two ago, Nikhil Kumar showed me this awesome real-time cartogram of twitter feeds. Since it was something I had no idea how to do, I thought it was a good time to learn. I decided to play around with geographical data visualizations and see what kind of graphics could be easily produced. Continue reading