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Unformatted text preview: Monday, Jan 10th 1. Basic concepts: Uncertainty / Randomness: The lack of certainty, a state of having limited knowledge where it is impossible to exactly de scribe current state or future outcome, more than one possible outcome (Doug Hubbard). From the point of view of physics, randomness is exactly opposite to the deterministicity. Uncertainty originated from philosophy, and exists in many aspects of science, business, and daily life. It appears in all areas of computer science and engineering as well. 2. Examples for randomness: 1. Coin toss 2. Rolling Dices, lottery 3. RNG (random number generation) 4. Weather prediction (mix of randomness and determinisitics) 5. Time consumed to load a webpage by di erent browser. 6. Brownian motion More examples in the textbook and lecture notes. 3. Mathematical models Probability and statistics are used to study the randomness / uncertainty sys tematically. They are invented to study physical process that are not completely determinisitic, and help to extrapolate the nature of randomness of those process and provide reliable prediction or summation. Probability : mathematical theory for modeling experiments where outcomes occur randomly Statistics : theory of information that uses data to make inferences about questions of interest, under the assumption that there is a random component to the process that generated the data.random component to the process that generated the data....
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 Spring '11
 Zhou
 Probability, Probability theory, Randomness, WSJ

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