5. [Section 4.9] The number of traffic accidents in Berkeley in 10 randomly chosen non-rainy days in 1998, which can be modeled as a Poisson distribution, is as follows: 4, 0, 6, 5, 2, 1, 2, 0, 4, 3 a. Derive the maximum likelihood estimate Å for a Poisson distribution. b. Use the data to estimate the proportion of non-rainy days that had 2 or fewer accidents that year.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
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Chapter10: Statistics
Section10.4: Distributions Of Data
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5. [Section 4.9] The number of traffic accidents in Berkeley in 10 randomly chosen non-rainy days in
1998, which can be modeled as a Poisson distribution, is as follows:
4, 0, 6, 5, 2, 1, 2, 0, 4, 3
a.
b.
Derive the maximum likelihood estimate å for a Poisson distribution.
Use the data to estimate the proportion of non-rainy days that had 2 or fewer accidents that
year.
Transcribed Image Text:5. [Section 4.9] The number of traffic accidents in Berkeley in 10 randomly chosen non-rainy days in 1998, which can be modeled as a Poisson distribution, is as follows: 4, 0, 6, 5, 2, 1, 2, 0, 4, 3 a. b. Derive the maximum likelihood estimate å for a Poisson distribution. Use the data to estimate the proportion of non-rainy days that had 2 or fewer accidents that year.
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