An Insurance company has developed the following table to describe the distribution of automobile collision claims paid during the past year. Payment ($) 0 500 average 1,000 2,000 5,000 8,000 10,000 Probability 0.85 0.06 0.03 0.02 0.02 0.01 0.01 (a) Set up a table of intervals of random numbers ranging from 0 to 1 that can be used with the Excel VLOOKUP function to generate values for automobile collision claim payments. Lower End of Interval Upper End of Interval Payment($) 0 500 1,000 2,000 5,000 8,000 10,000 (b) Construct a simulation model to estimate the average claim payment amount (in $) and the standard deviation (In $) in the claim payment amounts. (Use at least 1,000 trials. Round your answers to two decimal places.) 12:05 PM

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An insurance company has developed the following table to describe the distribution of automobile collision claims pald during the past year.
Payment ($)
(b)
0
500
1,000
2,000
5,000
8,000
10,000
Probability
0.85
0.06
0.03
0.02
$
0.02
0.01
(a) Set up a table of intervals of random numbers ranging from 0 to 1 that can be used with the Excel VLOOKUP function to generate values for automobile collision claim payments.
0.01
Lower End of Interval
NICO
Upper End of Interval Payment ($)
0
500
1,000
2,000
5,000
8,000
10,000
Construct a simulation
model to estimate the average claim payment amount (in $) and the standard deviation (in $) in the claim payment amounts. (Use at least 1,000 trials. Round your
answers to two decimal places.)
average
12:05 PM
Transcribed Image Text:An insurance company has developed the following table to describe the distribution of automobile collision claims pald during the past year. Payment ($) (b) 0 500 1,000 2,000 5,000 8,000 10,000 Probability 0.85 0.06 0.03 0.02 $ 0.02 0.01 (a) Set up a table of intervals of random numbers ranging from 0 to 1 that can be used with the Excel VLOOKUP function to generate values for automobile collision claim payments. 0.01 Lower End of Interval NICO Upper End of Interval Payment ($) 0 500 1,000 2,000 5,000 8,000 10,000 Construct a simulation model to estimate the average claim payment amount (in $) and the standard deviation (in $) in the claim payment amounts. (Use at least 1,000 trials. Round your answers to two decimal places.) average 12:05 PM
(b) Construct a simulation model to estimate the average claim payment amount (in $) and the standard deviation (in $) in the claim payment amounts. (Use at least 1,000 trials. Round your
answers to two decimal places.)
average
standard deviation
$
$
.., X, represent possible values of X. Then, the mean (u) and
√√(x₁ -μ)² x P(X = X₁) + ... + (x µ)² x P(X = X). Using these formulas, calculate
(c) Let X be the discrete random variable representing the dollar value of an automobile collision claim payment. Let, X₁, X₂¹
standard deviation (o) of X can be computed as μ = x₁ x P(X = X₁) + + x₁ x P(X = X ), and o =
Xn
the mean and standard deviation (In $). (Round your standard deviation to two decimal places.)
μ = $
0 = $
Compare the values of sample mean and sample standard deviation In part (a) to the analytical calculation of the mean and standard deviation. How can we Improve the accuracy of the
sample estimates from the simulation?
We can use a different discrete distribution to generate our random variables.
O We can decrease the number of simulation trials.
We can gather our data from real world samples instead.
We can increase the number of simulation trials.
We can use a different continuous distribution to generate our random variables.
Transcribed Image Text:(b) Construct a simulation model to estimate the average claim payment amount (in $) and the standard deviation (in $) in the claim payment amounts. (Use at least 1,000 trials. Round your answers to two decimal places.) average standard deviation $ $ .., X, represent possible values of X. Then, the mean (u) and √√(x₁ -μ)² x P(X = X₁) + ... + (x µ)² x P(X = X). Using these formulas, calculate (c) Let X be the discrete random variable representing the dollar value of an automobile collision claim payment. Let, X₁, X₂¹ standard deviation (o) of X can be computed as μ = x₁ x P(X = X₁) + + x₁ x P(X = X ), and o = Xn the mean and standard deviation (In $). (Round your standard deviation to two decimal places.) μ = $ 0 = $ Compare the values of sample mean and sample standard deviation In part (a) to the analytical calculation of the mean and standard deviation. How can we Improve the accuracy of the sample estimates from the simulation? We can use a different discrete distribution to generate our random variables. O We can decrease the number of simulation trials. We can gather our data from real world samples instead. We can increase the number of simulation trials. We can use a different continuous distribution to generate our random variables.
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