Archive for category pop
A Santa Claus machine
Someone just sent me this amazing video of a 3D printer copying a crescent wrench – moving parts and all. The company featured, Z-Corp, is a Stat-Ease client. See this case study showing how their engineers used response surface methods (RSM) to discover a small window of operability.
Another client of Stat-Ease, Stratasys, also offers rapid-prototyping machines, but they make use of another technology called fused deposition modeling (FDM) – explained nicely by this schematic from Ferris State University. I’ve seen these machines at work. They run from plastic line similar to what’s used in a weed whacker. Based on a computerized blueprint, this material (suitable for functional parts, not just prototypes) is melted layer-by-layer into complex shapes. Check out this full-scale turboprop engine produced by FDM.
The next step will be the development of machines that can make whatever you need out of whatever you happen to have nearby that can be shoveled in the hopper. Then people who really want to get away from the crowds can rocket off to any old unoccupied planetismal and set themselves up with house and home.
“It’s possible to imagine a machine that could scoop up material – rocks from the Moon or rocks from asteroids – process them inside and produce just about any product: washing machines or teacups or automobiles or starships. Once such a machine exists it could gather sunlight and materials that it’s sitting on, and produce on call whatever product anybody wants to name, as long as somebody knows how to make it and those instructions can be given to the machine. I think the name Santa Claus Machine for such a device is appropriate.”
– Physicist Theodore Taylor (1978)
Commuting by car or bike: Studies by UK statisticians
This month’s issue (June 2011, volume 8, issue 2) of the Royal Statistical Society magazine Significance [motto “statistics making sense” 🙂 ] features two intriguing articles on commuting.
The first one details Martin Griffiths, a math lecturer at U Manchester, “trying to pull out of the drive” (pp 89-91). This poor fellow must wait upwards of 2 minutes just to get on the road from his property. Imagine the frustration of a somewhat random stream of cars blocking your way out. Then, just as you see a gap, another car comes along to fill it. Griffiths provides a very impressive formula for average wait time based on a Poisson distribution. He factors in the average number of cars passing by as well as the time taken to pull out into the flow. The bottom line: It does not pay to be timid. You’d best mind the gap (inside joke for anyone who’s traveled London’s subways) and make a move!
The second study* comes from a biker, Dr. Jeremy Groves, who spends up to 2 hours or more commuting to his work at Chesterfield Royal Hospital. Thankfully his ride gets considerably shorter in summer when he needn’t wear baggy outerwear, which creates a real drag (Groves estimates 30% more wind resistance). This cycling enthusiast bought a new bicycle recently – one that featured a carbon frame, as opposed to the steel one he’d bought second-hand. Being a fan of randomized (“randomised” in UK spelling) trials, Groves completed a series of runs with one or the other of his bikes – measuring the times taken for the ride from his home in Sheffield to his work at hospital. Seeing his run chart starting off very raggedly at the high end in January, I transcribed only the latter 28 runs (14 of each) for the chart shown. 
Obviously from the overlap in the least-signficant-difference (LSD) bars the results remain inconclusive. (If you have trouble seeing this, click the graph for a larger view of it.) The difference is less than 1 minute in favor of the very costly carbon-framed bicycle. Given a 3.5 minute standard deviation under summer conditions, it would take 400 total runs (200 each) to resolve whether this is a true advantage, according to a power calculation I did with the aid of Design-Expert® software. Dr. Groves has moved on to another experiment for this summer – he plans to randomly load a 4 kg weight on his bicycle (the carbon one, I presume). Aside from being a glutton for punishment, I suppose this fellow wonders how much it slows him down when he must carry in his laptop.
* “Bicycle weight and commuting time: A randomised trial,” pp95-96.
Fun summer-time experiment: Super-cool beer so it instantly freezes solid
It turns out that if a bottle of beer is put in the freezer for long enough, and then removed while it is still liquid and, lastly, given a sudden shock, the beer will instantly freeze solid. I saw this confirmed by the pop-science TV show Mythbusters in their episode 153, originally aired on 11/10/10. Based on trial-and-error experimentation their Build Team found that 3 hours of cooling time sufficed to create the delightful phenomenon. See the instant beer-freeze demonstrated by EasyBarTricks.com here. For detailed instructions on how to try this at home or in a classroom, plus a nerdy explanation (think PVNERT) by physics and math teacher Daryl Taylor, check out this website.
Of course I had to try this for myself. However, not being one who ever leaves well-enough alone, I tried light beer (Miller, bottled in clear glass) side by side with the recommended Corona – two of each. Could this be a factor (light versus regular brew)? After being careful to wait at least 3 hours for the quartet of brews to super-cool, I brought them out for a family party. Two of the beers crystallized when smacked on our kitchen cutting board, but the other two did not. Here’s a twist, though: None of the bottles were uncapped first, so how does that gibe with the PV-nerd’s explanation?
Alas, one of the light beers crystallized and the other did not – ditto for the Corona, so my results, albeit semi-successful, were indeterminate on the issue of light vs regular brews. The good news is that we salvaged two bottles of beer (the frozen ones become undrinkable).
Feel free to weigh in with your theories and experimental results from this beer trick. One thing I learned from my first try – a lot more beer would be good, along with a walk-in freezer (or the backyard in mid-winter).
An Easter experiment for those who still believe a bunny bears eggs* *(Beware of the green ones!)
Today’s Saint Paul Pioneer Press “Bulletin Board” provides an idea on how to provide some added delight for any children who still believe in the Easter Bunny: Have them plant one of their jelly beans, then watch for it to grow into a lollipop. Doesn’t that sound like a fun experiment!
By the way, be careful with the green jelly beans – they cause acne (p<0.05) according to this exhaustive statistical-study of every available color.
Fun graphs and charts on names: How popular is yours and where is it populated?
My latest issue of National Geographic came with this fascinating mapping of population by surname. Seeing “Anderson” looming large over Minnesota did not surprise me, but I didn’t realize how many of us “snow birds” had permanently escaped to California. Take a look and see if you can locate any of you long-lost wander-kin around the USA.
The Junk Charts blog, one of my favorites, gave a generally favorable review of the “Nat-Geo” name chart, but they recommended an even-better one – the Baby Name Wizard, which plots the popularity of first names over the last 130 years.
I am expecting my first grandchild this summer, so there’s been lots of talks about names lately, thus this statistical chart caught my eye. You, too, may find it interesting. I suggest you start by hovering mouse over the widest streams (blue for boy, pink for girl) at the left (John, Mary, etc)* and then see how their popularity changes over the past 130 years. A tip: Click the graph to see trends for any given name, or enter it directly. Press “x” to get out of any specific name field (or type in another). I typed in my name and saw an explosion of popularity in mid-20th century, but now it’s fading away. The same holds true for my sister Nancy and my wife Karen – we all get tagged as baby-boomers straight away.
If you think there’s any chance of your name ranking in the top 1,000 for popularity in the USA at any time since 1880, type it in. How do you do, _______ (<= name here)?