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###### Suppose that the number of dropped calls on your cell phonevaries, with an average of 2.1 calls per day. If we assume that thePoisson setting is reasonable for this situation, we can model thedaily count of dropped calls X using the Poisson distribution withÂµ = 2.1.In this setting, the probabilities for 0, 1, 2, and 3 or moredropped calls are 0.1225, 0.2572, 0.2700, and 0.3503, respectively.Suppose that you record the number of dropped calls per day for thenext 100 days. Your observed counts of

Suppose that the number of dropped calls on your cell phone varies, with an average of 2.1 calls per day. If we assume that the Poisson setting is reasonable for this situation, we can model the daily count of dropped calls X using the Poisson distribution with Âµ = 2.1. In this setting, the probabilities for 0, 1, 2, and 3 or more dropped calls are 0.1225, 0.2572, 0.2700, and 0.3503, respectively. Suppose that you record the number of dropped calls per day for the next 100 days. Your observed counts of dropped calls are 11, 22, 28, and 39, respectively. Use a chi-square goodness of fit test to test the hypothesis that your calls are distributed according to this Poisson distribution. (calculate by hand)

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