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Random Processes - RSLAB-NTU
Random Processes - RSLAB-NTU

Stat 110 Midterm Review, Fall 2011
Stat 110 Midterm Review, Fall 2011

... for the exam, so please be there and arrive on time! Cell phones must be o↵, so it is a good idea to bring a watch. No books, notes, or calculators are allowed, except that you may bring two sheets of standard-sized paper (8.5” x 11”) with whatever you want written on it (two-sided): notes, theorems ...
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... formal models and verification techniques for real-time systems such as communication protocols, digital circuits with uncertain delay lengths, and media synchronization protocols. Automatic verification of quantitative timing constraints has particularly been subject to significant attention, as in ...
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... follow the binomial probability distribution with parameters n (number of trials) and p (probability of success). We call X the binomial random variable. * The terms success and failure are simply statistical terms, and do not have positive or negative implications. In a production setting, finding ...
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... role in the historical development of probability. The famous letters between Pascal and Fermat, which many believe started a serious study of probability, were instigated by a request for help from a French nobleman and gambler, Chevalier de Méré. It is said that de Méré had been betting that, ...
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... intensity that occurs within a given storm to estimate parameters of functions that describe susceptibility to windthrow, as a function of variation in storm severity and individual ...
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Discrete probability distributions
Discrete probability distributions

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Probability

Probability is the measure of the likeliness that an event will occur. Probability is quantified as a number between 0 and 1 (where 0 indicates impossibility and 1 indicates certainty). The higher the probability of an event, the more certain we are that the event will occur. A simple example is the toss of a fair (unbiased) coin. Since the two outcomes are equally probable, the probability of ""heads"" equals the probability of ""tails"", so the probability is 1/2 (or 50%) chance of either ""heads"" or ""tails"".These concepts have been given an axiomatic mathematical formalization in probability theory (see probability axioms), which is used widely in such areas of study as mathematics, statistics, finance, gambling, science (in particular physics), artificial intelligence/machine learning, computer science, game theory, and philosophy to, for example, draw inferences about the expected frequency of events. Probability theory is also used to describe the underlying mechanics and regularities of complex systems.
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