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Given that \( \mathrm{x} \) has a Poisson distribution with \( \mu=1.9 \), what is the probability that \( \mathrm{x}=2 \) ? \( P(2) \approx \) (Round to four decimal places as needed.)

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Final Answer:


\( P(\mathrm{x}=2) \approx 0.2642 \)

Step-by-step explanation:

The probability mass function (PMF) for a Poisson distribution is given by
\( P(\mathrm{x}=k) = (e^(-\mu) \mu^k)/(k!) \), where \( \mu \) is the mean of the distribution. In this case,
\( \mu = 1.9 \) and we want to find
\( P(\mathrm{x}=2) \). Substituting the values, we get:


\[ P(\mathrm{x}=2) = (e^(-1.9) \cdot 1.9^2)/(2!) \]

Calculating this expression yields the final probability. Utilizing the exponential function, factorial, and the given mean, the calculation provides
\( P(\mathrm{x}=2) \approx 0.2642 \).

Poisson distributions are often used to model the number of events occurring in a fixed interval of time or space. In this context,
\( P(\mathrm{x}=2) \) represents the probability of observing exactly 2 events when the mean rate is 1.9. This probability is obtained by considering the likelihood of observing a specific number of events in a Poisson process. The formula encapsulates the balance between the rate of occurrence
(\( \mu \)) and the specific outcome k, providing a precise probability for the given scenario.

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