9.36 Goodness of fit to a Poisson distribution. Referto Example 5.30 (page 329) where a Poisson distributionis described as a model for the number of dropped callson your cellphone per day. The mean number of callsis 2.1. In this setting, the probabilities for 0, 1, 2, and 3or more dropped calls are 0.1225, 0.2572, 0.2700, and0.3503, respectively. Suppose that you record the numberof dropped calls per day for the next 100 days. Yourobserved counts of dropped calls are 11, 22, 28, and 39,respectively. Use a chi-square goodness of fit test to testthe hypothesis that your calls are distributed according tothis Poisson distribution. EXAMPLE 5.30Number of dropped calls. Suppose that the number of dropped calls onyour cell phone varies, with an average of 2.1 calls per day. If we assumethat the Poisson setting is reasonable for this situation, we can modelthe daily count of dropped calls X using the Poisson distribution with= 2.1. What is the probability of having no more than two dropped callstomorrow?We can calculate P(X ≤ 2) either using software or the Poisson probabil-ity formula. Using the probability formula:P(X ≤2) = P(X= 0) + P(X = 1) + P(X = 2)e-2.1 (2.1)⁰ e 2.1 (2.1)¹ e 2.1 (2.1)²++1!2!===O!0.1225 +0.2572 +0.27000.6497Using the R software, the probability isdpois (0,2.1) + dpois(1,2.1) + dpois(2,2.1)[1] 0.6496314

The given probabilities for 0, 1, 2, and 3 or more dropped calls are 0.1225, 0.2572, 0.2700, and…

Answered: 9.36 Goodness of fit to a Poisson…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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