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4 February, 23:46

According to email logs, one employee at your company receives an average of 2.15 emails per week. Suppose the count of emails received can be adequately modeled as a Poisson random variable.

a. What is the distribution of the number of emails in a two-week period?

b. What is the probability of receiving 4 or fewer emails in a two-week period?

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  1. 5 February, 01:58
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    Answer:a) P (x=r) = e^-4.3 * 4.3^r / (r!), b) 0.7637

    Step-by-step explanation: The employee receives an average of 2.15 emails in one week.

    This is the constant rate at which the event is occurring and it does not affect any other.

    Hence λ = 2.15.

    If she receives 2.15 emails in 1 week, then in 2 week, she will receive an average of 2.15*2 = 4.3.

    Hence for the 2 week period, λ = 4.3 (that's she receives and average of 4.3 emails in 2 weeks).

    a) the probability distribution that defines a possion probability distribution is given below as

    P (x=r) = e^-λ * λ^r / (r!)

    Our question is to get the distribution, hence our answer will be in terms of r and λ = 4.3

    P (x=r) = e^-4.3 * 4.3^r / (r!)

    b) P (4 or fewer emails) = P (x≤4)

    P (x≤4) = P (x=4) + P (x=3) + P (x=2) + P (x=1) + P (x=0)

    Recall that

    P (x=r) = e^-4.3 * 4.3^r / (r!)

    At x = 4

    P (x=4) = e^-4.3 * 4.3^4 / (4!)

    P (x=4) = e^-4.3 * 4.3^4/24

    P (x=4) = 0.3866

    At x = 3

    P (x=3) = e^-4.3 * 4.3^3 / (3!)

    P (x=3) = e^-4.3 * 4.3^3 / (6)

    P (x=3) = 0.1798.

    At x = 2

    P (x=2) = e^-4.3 * 4.3^2 / (2!)

    P (x=2) = e^-4.3 * 4.3^2 / (2)

    P (x=2) = 0.1254

    At x = 1

    P (x=1) = e^-4.3 * 4.3^1 / (1!)

    P (x=1) = e^-4.3 * 4.3^1 / (1)

    P (x=1) = 0.0583

    At x = 0

    P (x=0) = e^-4.3 * 4.3^0 / (0!)

    P (x=0) = e^-4.3 * 1 / (1)

    P (x=0) = 0.0136

    P (x≤4) = 0.3866+0.1798+0.1254+0.0583+0.0136 = 0.7637
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