4.2. Example. The number of accidents that occur during a given month at a particular intersec- tion, X, tabulated by a group of Boy Scouts over a long time period is found to have a mean of 12 and a standard deviation of 2. The underlying distribution is not known. What is the probability that, next month. X will be greater than eight but less than sixteen. We thus want P[8 < X < 16]. 1 P [(µ – ko) < X < (µ + kµ)] > 1 k2 For this problem u = 12 and o = 2 so µ – ko = 12 - 2k. We can solve this equation for the k that gives us the desired bounds on the probability.

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4.2. Example. The number of accidents that occur during a given month at a particular intersec-
tion, X, tabulated by a group of Boy Scouts over a long time period is found to have a mean of 12
and a standard deviation of 2. The underlying distribution is not known. What is the probability
that, next month. X will be greater than eight but less than sixteen. We thus want P[8 < X < 16].
1
P [(µ
ko) < X < (µ + k µ)] > 1 –
k2
For this problem u = 12 and o = 2 so u – ko = 12 - 2k. We can solve this equation for the k that
gives us the desired bounds on the probability.
Transcribed Image Text:4.2. Example. The number of accidents that occur during a given month at a particular intersec- tion, X, tabulated by a group of Boy Scouts over a long time period is found to have a mean of 12 and a standard deviation of 2. The underlying distribution is not known. What is the probability that, next month. X will be greater than eight but less than sixteen. We thus want P[8 < X < 16]. 1 P [(µ ko) < X < (µ + k µ)] > 1 – k2 For this problem u = 12 and o = 2 so u – ko = 12 - 2k. We can solve this equation for the k that gives us the desired bounds on the probability.
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