Show transcribed image text The article "Expectation Analysis of the Probability of Failure for Water Supply Pipes" T proposed using the Poisson distribution to model the number of failures in pipelines of various types. Suppose that for cast-iron pipe of a particular length, the expected number of failures is 1 (very close to one of the cases considered in the article). Then X, the number of failures, has a Poisson distribution with μ = 1· (Round your answers to three decimal places.) (a) Obtain P(X S 5) by using the Cumulative Poisson Probabilities table in the Appendix of Tables. (b) 2) from the pmf formula. Determine P(X P(X = 2) = Determine P(X = 2) from the Cumulative Poisson Probabilities table in the Appendix of Tables. P(X= 2) = (c) Determine P(2 SX4) P(2 X 4)= (d) What is the probability that X exceeds its mean value by more than one standard deviation?
The article "Expectation Analysis of the Probability of Failure for Water Supply Pipes" T proposed using the Poisson distribution to model the number of failures in pipelines of various types. Suppose that for cast-iron pipe of a particular length, the expected number of failures is 1 (very close to one of the cases considered in the article). Then X, the number of failures, has a Poisson distribution with μ = 1· (Round your answers to three decimal places.) (a) Obtain P(X S 5) by using the Cumulative Poisson Probabilities table in the Appendix of Tables. (b) 2) from the pmf formula. Determine P(X P(X = 2) = Determine P(X = 2) from the Cumulative Poisson Probabilities table in the Appendix of Tables. P(X= 2) = (c) Determine P(2 SX4) P(2 X 4)= (d) What is the probability that X exceeds its mean value by more than one standard deviation?
