More fun with statistics, beware your kitchen appliances

Via Bruce Schneier, there is this quite good write up on risk assessment in the government.  Apparently, most government agencies actually have explicit risk metrics when allocating resources based on the chance of things causing human fatalities:

An unacceptable risk is often called de manifestis, meaning of obvious or evident concern — a risk so high that no “reasonable person” would deem it acceptable. A widely cited de manifestis risk assessment comes from a 1980 United States Supreme Court decision regarding workers’ risk from inhaling gasoline vapors. It concluded that an annual fatality risk — the chance per year that a worker would die of inhalation — of 1 in 40,000 is unacceptable. This is in line with standard practice in the regulatory world. Typically, risks considered unacceptable are those found likely to kill more than 1 in 10,000 or 1 in 100,000 per year.

At the other end of the spectrum are risks that are considered acceptable, and there is a fair degree of agreement about that area of risk as well. For example, after extensive research and public consultation, the United States Nuclear Regulatory Commission decided in 1986 that the fatality risk posed by accidents at nuclear power plants should not exceed 1 in 2 million per year and 1 in 500,000 per year from nuclear power plant operations. The governments of Australia, Japan, and the United Kingdom have come up with similar numbers for assessing hazards. So did a review of 132 U.S. federal government regulatory decisions dealing with public exposure to environmental carcinogens, which found that regulatory action always occurred if the individual annual fatality risk exceeded 1 in 700,000. Impressively, the study found a great deal of consistency among a wide range of federal agencies about what is considered an acceptable level of risk.

This falls down when it comes to terrorism:

As can be seen, annual terrorism fatality risks, particularly for areas outside of war zones, are less than one in one million and therefore generally lie within the range regulators deem safe or acceptable, requiring no further regulations, particularly those likely to be expensive. They are similar to the risks of using home appliances (200 deaths per year in the United States) or of commercial aviation (103 deaths per year).

Hmmm… I’m going to have to start keeping an eye out on my dishwasher.  I’m pretty sure it has it in for me.

Relearned Linear Algebra

After nearly a month of tinkering with code, nearly giving up twice, and realizing that I was going to actually need to relearn my linear algebra to get a real solution, I managed to create this graph.  It is the position of the moons of Jupiter relative to the planet as seen from earth.

Thanks to Thor for helping me get to the realization that straight up geometry wasn’t going to be good enough, and help boot strap my relearning of vector math.  Once I started using real linear algebra I didn’t even have to cheat on generating the sign.  Next step… JNI.

Where have all the planets gone?

From the Journal of Improbable Research:

With the loss of Pluto, the number of major planets in our solar system has dropped to eight. If the current trend continues, then come April 13, 3703 the solar system will no longer have any major planets. My analysis suggests several possible causes, for the loss of major planets….

The moto of the Improbably Research Journal is: First it makes you laugh, then it makes you think.

The “makes you think” part here is realizing there was nothing sacred about the number 9 when it came to planets.  The number of planets has gone up and down in the past many times as we’ve learned more about our solar system.  This was well put by Darren Bennett’s Census of the Solar System last year in 365 Days of Astronomy.

I’m still more of a fan of the “enough gravity to make it round” view of planets, which give us dozens (possibly hundreds) of new planets, including turning the major moons of the gas giants into planets.  We’d need one hell of a mnemonic to keep track of them all, but I think even the current definition of planets is going to become problematic when we get more data on extra solar planets.  For those wondering, that number is currently 453 and growing.

XKCD color survey

When a blog post starts with the following:

Who in the rainbow can draw the line where the violet tint ends and the orange tint begins? Distinctly we see the difference of the colors, but where exactly does the one first blendingly enter into the other? So with sanity and insanity.
—Herman Melville, Billy Budd

Orange, red? I don’t know what to believe anymore!
—Anonymous, Color Survey

—Anonymous, Color Survey

and, it’s done by xkcd, you know it’s going to be good.

I actually had to stop reading for a bit, because I was laughing too hard that my eyes teared up.  The “unique color names” towards the end will make you fall out of your chair.

A snapshot of Dutchess County New York

After failing to convince a friend that his statement of “earning potential in the pure computer field in Dutchess county is around $27-30K at best” was both baseless, and entirely made up, I started trying to find some real data on what the answer was.  The fact that I just posted about the need for Data literacy made the event that much more ironic.

Along the way I found the Dutchess County Economic Development Corporation’s economic report.  It’s quite interesting, and gives a rather extensive set of data about the county, including housing and employment statistics.  Most of the data looks to be from 2008, though there are comments about updates in 2009.

And, at least a partial answer was found to the first question, on page 6 of the report, in the Representative Median Salaries 2008 section:

Computer Programmer – $82,690
Network Administrator – $61,210

Maybe it’s time to take a statistics class

From Wired’s Why We Should Learn the Language of Data:

Statistics is hard. But that’s not just an issue of individual understanding; it’s also becoming one of the nation’s biggest political problems. We live in a world where the thorniest policy issues increasingly boil down to arguments over what the data mean. If you don’t understand statistics, you don’t know what’s going on — and you can’t tell when you’re being lied to. Statistics should now be a core part of general education. You shouldn’t finish high school without understanding it reasonably well — as well, say, as you can compose an essay.

It goes on to explain a whole number of policy issues that are being argued with badly understood data.

On a related note: It’s dark out, that is proof the Sun has been destroyed.

Victory vs Pandemic

Pandemic is a really amazing game.  Instead of players playing against each other, you are playing against the game mechanics to try to cure the world of 4 diseases that are breaking out in different geographies.  Difficulty level can be adjusted by setting the frequency of the outbreaks.

The noob level of pandemic is 4 epidemics.  Susan and I can pretty much beat every instance of that.  Last night we managed our first victory at the 5 epidemic level (after a fare number of losses).  For anyone that knows the game, they’ll notice we were at our final outbreak level when we won.

Moving 1.2 Tera Bytes

Back of the envelope math is good to do.  I’m currently working to upgrade my raid array, but due to a lack of ports on the home server, I’m using a second box to build and initialize the new array.

1.2 Terrabytes / 100 Mbs network = 26 hours at theoretical peak performance.  I’m getting about 80% of peak, so just over 30 hours.  Ooof.