As mentioned in Section 4.5, when n is large, p is small, and np ≤ 7, the Poisson probability distribution provides a good approximation to the binomial probability distribution. Since we provide exact binomial probabilities (Table II in Appendix A) for relatively small values of n, you can investigate the adequacy of the approximation for n = 25. Use Table II to find p(0), p(1), and p(2) for n = 25 and p = .05. Calculate the corresponding Poisson approximations, using λ = μ = np. These approximations are reasonably good for n as small as 25, but to use such an approximation in a practical situation we would prefer to have n ≥ 100.
Answer to relevant QuestionsPenumbrol imaging is a technique used by nuclear engineers for imaging objects (e.g., X-rays and lasers) that emit high-energy photons. In IEICE Transactions on Information & Systems (Apr. 2005), researchers demonstrated ...Explain the difference between sampling with replacement and sampling without replacement. Refer to the Journal of Engineering, Computing and Architecture (Vol. 3., 2009) study of cell phone handoff behavior, Exercise 3.58 (p. 134). Recall that a “handoff” describes the process of a cell phone moving from one ...According to Brighton Webs LTD, a British company that specializes in data analysis, the arrival time of requests to a Web server within each hour can be modeled by a uniform distribution (www.brighton-webs.co.uk). ...Suppose x is a normally distributed random variable with μ = 30 and σ = 8. Find a value x0 of the random variable x such that a. P(x ≥ x0) = .5 b. P(x < x0) = .025 c. P(x > x0) = .10 d. P(x > x0) = .95
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