Another new tool found through the TED video I watched in class. http://www.gapminder.org/
So many tools, so little time.
Crossposted on Naked Capitalism
I recently was hugely flattered by my friend Cosma Shalizi’s articulate argument against my position that data science distinguishes itself from statistics in various ways.
Cosma is a well-read broadly educated guy, and a role model for what a statistician can be, not that every statistician lives up to hist standard. I’ve enjoyed talking to him about data, big data, and working in industry, and I’ve blogged about his blogposts as well.
That’s not to say I agree with absolutely everything Cosma says in his post: in particular, there’s a difference between being a master at visualizations for the statistics audience and being able to put together a power point presentation for a board meeting, which some data scientists in the internet start-up scene definitely need to do (mostly this is a study in how to dumb stuff down without letting it become…
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Added a new blog link. I never really figured if I should inform the blog owner that I am linking to them.
What lead me to this blog was his post on “R Code Style Guide“. Something I have neglected when writing my R scripts. It helps to have consistency in naming your variables, functions and constants – makes readability much better when you need to come back to the script after a while.
In the meantime, I am looking out for suitable Kaggle competitions to join for fun and learning.
Exploring and venting about quantitative issues
Using large digital libraries to advance literary history
Zoom out, zoom in, zoom out.
Blog to document and reflect on Columbia Data Science Class
A Quick-R Companion
[R] + applied economics.
Scientific computing, data viz and general geekery, with examples in R and MATLAB.