Randomness
From Maze
(Difference between revisions)
(→Randomness in Contemporary Computing (Sidebar)) | (→Randomness Comes to Computing) | ||
| Line 51: | Line 51: | ||
An obvious question to ask about randomness is why a computer would need to implement it in any form. Chance might produce stunning poetry, breathtaking art, uncanny music, and compelling games, but what is its role in the sciences? Why provide a calculating machine with the ability to generate random numbers in the first place? The stereotype of computing is that it is done exactly, repeatedly, with perfect precision and accuracy. Computers are supposed to order the world. Computers are supposed to sift through reams of data and model possible outcomes, possible futures, providing certain answers where there seem to be none. Yet a function to create random numbers was present in the first Dartmouth BASIC. Every version of BASIC since then has had one or more ways to create random numbers. Nearly every contemporary programming language, including Python, Perl, Java, JavaScript and C++, has a way to generate randomness. | An obvious question to ask about randomness is why a computer would need to implement it in any form. Chance might produce stunning poetry, breathtaking art, uncanny music, and compelling games, but what is its role in the sciences? Why provide a calculating machine with the ability to generate random numbers in the first place? The stereotype of computing is that it is done exactly, repeatedly, with perfect precision and accuracy. Computers are supposed to order the world. Computers are supposed to sift through reams of data and model possible outcomes, possible futures, providing certain answers where there seem to be none. Yet a function to create random numbers was present in the first Dartmouth BASIC. Every version of BASIC since then has had one or more ways to create random numbers. Nearly every contemporary programming language, including Python, Perl, Java, JavaScript and C++, has a way to generate randomness. | ||
| − | Quite simply, randomness is necessary for any statistical endeavor or any simulation that involves unknown variables. Practically ''everything'' involves unknown variables: the meteorological conditions at rocket launch site, the flow of air under a bomber's wings, and the vector of an infectious disease. Additionally, there is the flow of traffic, the cost of bread, and the drip of water from the kitchen faucet. Forecasting any of these phenomena requires reckoning with uncertainty, which in turn requires a pool of random numbers that can be plugged into sampling algorithms and tests of probability. One or two random numbers are not enough. Large-scale statistical calculations or simulations require large batches of random numbers. In Deborah Bennett's history of humans' quest for randomness -- which she suggests goes as far back as ancient Babylonia (17) -- she highlights one of the early and largest set of random numbers, ''A Million Random Digits with 100,000 Normal Deviates'' (135). Generated in 1955 "by random frequency pulses of an electronic roulette wheel" by the very appropriately-named RAND Corporation, this series of numbers was an important contribution to any study of probability and is still in use today. As the forward to the undated online edition of the table notes: | + | Quite simply, randomness is necessary for any statistical endeavor or any simulation that involves unknown variables. Practically ''everything'' involves unknown variables: the meteorological conditions at rocket launch site, the flow of air under a bomber's wings, and the vector of an infectious disease. Additionally, there is the flow of traffic, the cost of bread, and the drip of water from the kitchen faucet. Forecasting any of these phenomena requires reckoning with uncertainty, which in turn requires a pool of random numbers that can be plugged into sampling algorithms and tests of probability. One or two random numbers are not enough. Large-scale statistical calculations or simulations require large batches of random numbers. In Deborah Bennett's history of humans' quest for randomness -- which she suggests goes as far back as ancient Babylonia (17) -- she highlights one of the early and largest set of random numbers, ''A Million Random Digits with 100,000 Normal Deviates'' (135). Generated in 1955 "by random frequency pulses of an electronic roulette wheel" by the RAND Corporation, an research and development think tank funded in part by the Air Force, this series of numbers was an important contribution to any study of probability and is still in use today. As the forward to the undated online edition of the table notes: |
<blockquote>The tables of random numbers in the book have become a standard reference in engineering and econometrics textbooks and have been widely used in gaming and simulations that employ Monte Carlo trials. Still the largest known source of random digits and normal deviates, the work is routinely used by statisticians, physicists, polltakers, market analysts, lottery administrators, and quality control engineers.</blockquote> | <blockquote>The tables of random numbers in the book have become a standard reference in engineering and econometrics textbooks and have been widely used in gaming and simulations that employ Monte Carlo trials. Still the largest known source of random digits and normal deviates, the work is routinely used by statisticians, physicists, polltakers, market analysts, lottery administrators, and quality control engineers.</blockquote> | ||
