Data

Data

There are few things in life that I enjoy more than a good set of data. Say what you will about me, but that’s the truth. I spend an inordinate amount of time parsing over tables of all different types of information.

I frequently find myself correlating some data source with some other and making various conclusions from this. I figure I might as well share some. First up: the disproving of the popular adage “Money can’t buy happiness.” According to the American population, oh yes it can.

AHIP surveys 1000 Americans almost every day of the year (350/365 days) and asks them a bunch of census-type questions and a bunch of “how was your day?” type questions. From this we can correlate their “well-being” with their income. It looks like so:

money-happiness

Each data point represents a single congressional district. The line is a exponential fit. I was actually surprised with the shape of the curve. I would have expected even more of a plateau at some reasonable amount of income above the poverty line — say $40k. Instead we see that as you make more money you just become happier. Obviously when the y-axis is set to a logarithmic scale this then becomes a linear relationship so it takes and ever increasing amount of money to keep moving up the happiness scale.

Interestingly, this survey somehow gets away with random dialing cell phone numbers as well as land lines to keep the number as unbiased as possible. I didn’t know that was possible. I thought random dialing cell phones was against some law or another.

Oh, and in case you were wondering: 6 of the 10 highest ranked Congressional Districts are in CA, with #1 being the Peninsula in the Bay Area, who also takes #1 in Best Work Environment and #2 in Healthy Behavior.