In a residential section of Indiana, the number of vehicular accidents between 8 AM and 6 PM during the week has been averaging 3 and a Poisson distribution is a reasonable approximation to the distribution of weekly accidents. A traffic engineer thought that installing speed humps may lower the average to 1.5 and expressed her uncertainty with a Gamma(3,2) distribution for that average. After installation, the numbers of weekly accidents for five weeks in a row were 6, 2, 1, 5, and 2. Given these data and her prior belief, what is her updated estimate of the average number of accidents per week, namely the expected accident rate?

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In a residential section of Indiana, the number of vehicular accidents between 8 AM and 6 PM
during the week has been averaging 3 and a Poisson distribution is a reasonable approximation to
the distribution of weekly accidents. A traffic engineer thought that installing speed humps may
lower the average to 1.5 and expressed her uncertainty with a Gamma(3,2) distribution for that
average. After installation, the numbers of weekly accidents for five weeks in a row were 6, 2, 1, 5,
and 2. Given these data and her prior belief, what is her updated estimate of the average number of
accidents per week, namely the expected accident rate?
Transcribed Image Text:In a residential section of Indiana, the number of vehicular accidents between 8 AM and 6 PM during the week has been averaging 3 and a Poisson distribution is a reasonable approximation to the distribution of weekly accidents. A traffic engineer thought that installing speed humps may lower the average to 1.5 and expressed her uncertainty with a Gamma(3,2) distribution for that average. After installation, the numbers of weekly accidents for five weeks in a row were 6, 2, 1, 5, and 2. Given these data and her prior belief, what is her updated estimate of the average number of accidents per week, namely the expected accident rate?
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