Chapter 9 A SURVEY OF SYNOPSIS CONSTRUCTION IN DATA STREAMS Abstract The large volume of data streams poses unique space and time constraints on the computation process. Many query processing, database operations, and mining algorithms require efficient execution which can be difficult to achieve with a fast data stream. In many cases, it may be acceptable to generate approximate solutions for such problems. In recent years a number of synopsis structures have been developed, which can
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Calculator: hand-held with keys for natural logarithm, mean, and standard deviation Course Description: The role of statistical evidence in the formation of inference and in the selection of strategies in solving business problems is developed. Probability and probability distributions are studied as a basis of statistical inference. An introduction to multivariate analysis is provided, which includes analysis of variance and regression methods. Specifically, the course covers in order most of the material
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probabilistic. Steps: * Establish the probability distribution for each random variable. * Use random numbers to generate random values. * Repeat for some number of replications. Probability Distributions: Historical data Goodness-of-fit tests for common distributions: * Normal * Uniform * Exponential * Poisson * Binomial Role of Computers: * Built-in random number procedures for simulating from several different probability distributions. * Easy and fast
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represents the number of people in the population without the disease. • Let n denote the number of samples in a group. Therefore, [pic] be the number of groups. Let ‘p’ represent the probability that a group tests negative for the disease, that is, none of the group members carry the antigen. Probability Distribution In a population of N, there are r people who carry the disease and N-r people who are free from the disease. Samples of size n are chosen from this population. Let X denote
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random sample of size 5 + 50 + 100 + 345 = 500 is obtained. c) Why is the sampling in (a) not simple random sampling? In simple random sampling all possible samples of size 500 are given the same probability of being selected. In stratified random sample, this not the case. For example the probability of selecting 500 invoices from stratum 4 is 0. Only 345 invoices are selected from stratum 4. The NBC hit comedy Friends was TiVo's most popular show during the week of April 18-24, 2004. According
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project; The critical path of the project; The required starting time and finish time of each task; Probabilities of finishing project on a certain date; ... ■ Output: – – – – – PERT/CPM is supposed to answer questions such as: ■ How long does the project take? ■ What are the bottle-neck tasks of the project? ■ What is the time for a task ready to start? ■ What is the probability that the project is finished by some date? ■ How additional resources are allocated among the tasks
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with rate parameter R and shape parameter k, the density of T is given by R(Rt)kϪ1eϪRt f (t) ϭ ᎏᎏ (k Ϫ 1)! (t Ն 0) and k E(T) ϭ ᎏᎏ R and k var T ϭ ᎏᎏ R2 Birth–Death Processes For a birth-death process, the steady-state probability (pj) or fraction of the time that the process spends in state j can be found from the following flow balance equations: ( j ϭ 0) ( j ϭ 1) ( j ϭ 2) и и и ( jth equation) p0l0 ϭ p1m1 (l1 ϩ m1)p1 ϭ l0p0 ϩ m2p2 (l2 ϩ m2)p2 ϭ l1p1 ϩ m3p3
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deviation of returns to measure the variability, hence the risk of an asset. Possible Return Probability of Occurrence (Project A) Probability of Occurrence (Project B) -0.1 0.05 0.01 -0.02 0.1 0.03 0.04 0.2 0.16 0.09 0.3 0.6 0.14 0.2 0.16 0.2 0.1 0.03 0.28 0.05 0.01 Returns could also take continuous values, in which case, a normal distribution of returns may be assumed and probabilities associated with range of values may be calculated. To compare the riskiness of alternatives of
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Modelling Football Data By Renzo Galea A Dissertation Submitted in Partial Fulfilment of the Requirements For the Degree of Bachelor of Science (Honours) Statistics and Operations Research as main area DEPARTMENT OF STATISTICS AND OPERATIONS RESEARCH FACULTY OF SCIENCE UNIVERSITY OF MALTA MAY 2011 Declaration of Authorship I, Renzo Galea 25889G, declare that this dissertation entitled: “Modelling Football Data”, and the work presented in it is my own. I confirm that:
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Acme Electronics Case Date: March 6, 2012 To: Jetson, on behalf of Acme Electronics From: Team 4 Consulting Firm Re: Legal and statistical evaluation of problems facing Acme Per your request, we have assembled a report with a legal and statistical evaluation of the problems facing Acme. If you have any questions, feel free to contact us at any time. Group 4: Acme Electronics Case Executive
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