Well, it’s a gloomy weekend here, but luckily I have a good book to curl up with, thanks to my fabulous younger brother. I’ve mentioned Nate Silver’s 538 blog as one of my favorites for breaking down election/political statistics, and it turns out he has a new book out. Before I could figure out if I wanted to buy it or not, it showed up at my door, courtesy of Amazon.com and my brother Tim. Review to follow I’m sure.
Next, I set up a new email address for this blog, in case any of my wonderful readers should stumble across any studies you think would work well on this site. My time has been a bit crunched post-baby, so I’d appreciate any interesting articles to spur more posting. If you see one, feel free to send it to baddatabad at gmail dot com (or hit the email me button on my profile).
That’s it for now, have a lovely weekend!
Numbers never lie.
Unlike people, who are constantly confused by their own biases and perspectives, numbers behave….if you know how to use them.
This is what I do for work every day:
First, I get what management thinks is the problem. Second, I talk to the people involved and find out what they think is the problem. Third, I get to retreat in to the numbers. I spend time looking at what we’re doing, where we are, and where we’d need to be for everyone to be happy. It’s the third part that’s my favorite. No one argues, no political pressure, just puzzles, problems, and unexpected truths.
I use data every day to help improve health care, and I’ve been pretty successful at it so far. As I look around though, I realize how few people really understand the importance of good data in our lives. One needs look no further than election year politics to see bad data, poor interpretations of good data, and blatant misuses that make me cringe. In the healthcare realm, we don’t have this luxury. I come from a world where you can’t take chances, where misrepresenting your stats can result in very real human suffering.
This is why improper uses of data drive me nuts. Once you know what to look for, it’s hard to stop seeing it. It’s everywhere. Thus, I am giving myself an ambitious goal. It’s no longer enough for me to use good data science for my own purposes. I want to educate others, and hone my own skills along the way. I want people to know what research is, how to read it, and how to question it. I want others to be as passionate as I am, and I want a place to vent about the reporting that annoys me.