Section 5 - CEE 3040 Fall 2009 CEE 304 Section 5 Review of...

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CEE 3040 Fall 2009 CEE 304 – Section 5 Review of Poisson Processes A Poisson process satisfies three conditions: 1. The probability of an arrival in a short interval t equals λ∆ t. For small t, the probability of 2 arrivals within t can be neglected. Here λ is the arrival rate with units per time, or counts per time. 2. The arrival rate λ is constant. 3. The number of arrivals in non-overlapping intervals are independent. Examples of Poisson Processes: 1. An engineer has instrumented several towers to measure wind gust speed and other parameters. Events of magnitude of interest occur on average once every 3 months. Assume the arrival of such events are a Poisson process, and the experiment lasts 18 months. a.) What is the mean and variance of the number of events that will occur? Solution: Mean = Var = 6 b.) What is the probability she sees 4 or fewer events during the 18 mo. experiment? Solution: Use Poisson tables: P[X ≤ 4 | ν = 6] = 0.285 c.) If she decided to run the experiment until 5 events are observed, what is the mean and variance of the length of the resulting experiment? Solution:
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This note was uploaded on 10/13/2010 for the course CEE 3040 at Cornell University (Engineering School).

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Section 5 - CEE 3040 Fall 2009 CEE 304 Section 5 Review of...

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