Here are the essential concepts you must grasp in order to answer the question correctly.
Poisson Distribution
The Poisson distribution is a probability distribution that expresses the probability of a given number of events occurring in a fixed interval of time or space, given a known average rate of occurrence. It is characterized by the parameter 'mu' (λ), which represents the average number of events in the interval. In this case, with mu = 4, it models the number of customers arriving at the checkout counters per minute.
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Mean (Expected Value)
The mean, or expected value, of a probability distribution is the long-term average value of repetitions of the experiment it represents. For the Poisson distribution, the mean is equal to the parameter mu (λ). In this scenario, a mean of 4 indicates that, on average, 4 customers arrive at the checkout counters each minute.
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Histogram
A histogram is a graphical representation of the distribution of numerical data, where the data is divided into bins or intervals. Each bin's height represents the frequency of data points within that interval. In this context, comparing the histogram of the Poisson distribution with the calculated probabilities helps visualize how the number of customers arriving aligns with the expected distribution.
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