Archive for April, 2007 Page 2 of 7



Logan Airport’s Rainbow Cove Green Parking Garage

Well, I’m just throwing that one post a day standard out the window, eh? [Imaginary Editor’s Note: Adam is not a Canadian although he uses “eh?” quite liberally] Well, breaking news of the sort you’re about to hear makes all standards completely invalid. Rainbow Cove Green

I’m proud to announce that Boston has set a new world record for the world’s largest version of the historically popular Tetris video game! The blocks are completely controlled by a Nintendo Wii controller and the gigantic Tetris installation is augmented by a giant speaker (not pictured) blasting the classic Tetris soundtrack.

Ok, ok…this picture really shows the newly redesigned Terminal C parking garage at Boston’s Logan Airport, but it sure does seem Christopher Janney, the structure’s architect, was heavily influenced by the colored tetrominoes in Tetris, eh? On record, Christopher states that he is influenced by sounds and how structures can act as a visual medium for sound. Apparently a trip in the structure’s elevator exposes you to natural sounds from New England that are supposed to interplay with the patterns created by the colored blocks.

Credit for the the picture of the real-life Tetri…I mean Rainbow Cove Green, goes to the book, Architecture of the Air: The Sound and Light Environments of Christopher Janneywith digital reproduction thanks to arcspace.com. I must also mention that I came across this picture via this article on Bostonist.com, where you can find a bit more information about the structure.

What do you think? Do the new parking garage structures at Logan Airport look like a huge version of Tetris? Do you like the design?

Similarities and Differences between the Standard Normal (z) and Student’s t Distributions

The requirements for this assignment were to compare and contrast the “…standard normal and the student t, or simply the t distribution. If we use the standard normal when σ [sigma, standard deviation] for the population is known and use the t distribution when σ is not known, explain any differences in the two distributions when n [sample size] <” 30? Explain why, using an example if necessary, there is not a difference between z and t when n > 30.” This assignment was the third written response for my Statistics II class (Quantitative Tools for Management) during the Spring 2007 semester at the University of Massachusetts at Amherst’s online program; I earned a 5/5 for the below response:

In general, as the sample size decreases in a t distribution, it becomes more and more similar to a z distribution. As the sample size increases, the standard deviation decreases in both z and t distributions. In essence, a larger sample size leads to a more accurate end result. The exponential decline in differences between the t and z distribution is an outcome of the central limit theorem. As the standard deviation decreases (due to the increased reliability of an increasingly larger sample size), the differences between the two distributions are so accurate that they both approximate a standard normal distribution.

In the real world, we see this principle in practice all the time, as I’ve mostly been a windows user, more time with Mac OS X will decrease the amount of times I use control-c for copy instead of apple-c; [although WebCT threw me for a loop since it still uses control-c as does OpenOffice.org]. It’s the basic concept behind learning, the more information you take in the smarter you’ll be until you’re very nearly perfect (time plays a factor as you can’t learn everything in a life time) and a very pervasive concept in business; the more cars Honda makes in the exact same manner, the fewer mistakes there’ll be. If their new plant made a car that wouldn’t start in their first batch of five cars, the 20% failure rate is not very indicative of Honda quality. You would expect that as they made a million of the same model they’re failure rate would be much, much lower. Each million cars produced should bring their failure rate closer to 0%. If it doesn’t then their is a flaw in the manufacturing process.

Freakonomics versus Economics

I usually won’t post twice in a day (or so I say), but a post entitled, What is it about Polish people and lines?, by Steven D. Levitt, co-author of the uber-popular, Freakonomics: A Rogue Economist Explores the Hidden Side of Everything, really got me ticked off tonight! Steven recently went on a trip to Warsaw (and did, rightfully, credit the city as being awesome) and found that Polish people everywhere where cutting ahead of him in line and worst of all, acting as if it was no big deal! Well, needless to say, Steven found this sort of behavior to be quite rude and impolite, considering he was patiently waiting in line and not cutting anyone the entire time.

Now, I wasn’t really upset that Steven called Polish people rude (or to be more accurate, categorized their line-cutting skills as rude); rather, I was upset that Steven didn’t see the basic supply and demand effect at play here! As I explained to my good friend, Lucy, an avid fan of Freakonomics, the demand can be seen by the line formed; in other words, if I walk up to an existing line and see that it is already quite lengthy, I automatically see that there is a high demand for whatever these people are waiting for. If I then hop in the line (without even knowing what I’m waiting for…this better be good), and see that in the short time span I’ve been waiting the line has almost doubled in size, my earlier observation that demand is high and thus the supply must be something good is (somewhat) confirmed. There are other clues to the demand we can gather from the line, such as how impatient or frenzied the people in the line are and the rate of the line’s growth.

The supply in Mr. Levitt’s situation is unknown; the purpose of the line is also unknown. Now a quick history lesson, not too long ago Poland was under communist rule and suffered through logistical problems constantly, such as insufficient supply of necessity items such as food and clean water (as did many communist nations). Under communist rule, and possibly in Steven’s situation, the supply was not known. Thus, everyone has to assume that the supply is not enough to satisfy everyone in the line. Since the true supply is not known, a rational person will assume there is not enough supply to go around, especially considering the apparent high demand as indicated by the long line (or because from past experiences during communist rule, there was never enough supply).

Thus, any reasonably rational person will cut the line as many times as they can in order to increase their chance at getting some of the supply. Having experienced terrible logistics during communist rule, the Poles have simply adapted to getting their share of the supply, by any and all means necessary. If you’d grown up under communist rule, always wondering if you’ll receive your fair share of food, wouldn’t you cut to gain an edge? If you and everyone else in the line believes the supply is rapidly depleting, and especially if it’s a crucial supply, food and water for example, you’d be an idiot to stand idly by while all the cutters get food and water to feed themselves and their family. It’s not just supply and demand, it’s survival of the fittest!

Many of the commenters on Mr. Levitt’s post have also pointed out that the Polish are not alone in their use of cutting; it is a very prevalent practice in much of the world, for example Brazil, China and Italy, and some countries, such as India are just a free for all with nary a line in sight (which makes sense considering the huge population there).

Again, I’m not upset that Steven Levitt called the Polish rude (we’ve been called much worse), but he missed the supply and demand effect here and the effect communism has had on Polish people’s behavior. To Steven’s credit, he does note towards the end of his post that he may have “got the theory backwards. With so many years of shortages, the rewards for becoming an expert line cutter were much greater in Poland than in the U.S. So they did perfect standing in lines — perfection means being able to cut in front of people and feel no guilt.” Still, it seems this note was added as an after-thought just to cover Mr. Levitt in both explanations.

Personally, I think the Polish people have have grown so fond of freedom and are so anti-establishment that they view cutting as a way to express their freedom. So, cut, cut away my fellow country-men; you’ll see me doing the same as much as possible here, it’s a great time-saver!

Finite Population Correction Factor

The assignment for this response was to discuss “…under what circumstances the Finite Population Correction Factor (FPCF) is necessary and why is it necessary? How does the adjusted z-value vary quantitatively (bigger, smaller, much larger, no change) from the normal value?” This was the first written response for my Statistics II class (actually called “Quantitative Tools for Management” in the course catalog, but it is roughly equivalent to a Stats II course) during the current semester (Spring 2007) at the University of Massachusetts at Amherst’s online program; I earned a 5/5 for my response below:

When a sample is greater than 5% of the population from which it is being selected and the sample is chosen without replacement, the finite population correction factor should be used. The adjusted z-value would be larger than the normal z-value, meaning that the value is more standard deviations from the middle than in a non-adjusted z-value.

This factor adjusts the z-value to show the extra precision obtained from the sample size being a greater fraction of the population size than normal. Since the standard deviation becomes smaller as the sample size increases, the FPCF shows that a value in a large sample size not at or near the mean is a greater number of standards deviations from the mean than in a small sample size. In other words it’s rarer for a value in a large sample size to be far away from the mean compared to a small sample size.






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