Explain why the probability mass function P(X = 1000) = 0.1, P(X = 1500) = 0.2,...
Explain why the probability mass function P(X = 1000) = 0.1, P(X = 1500) = 0.2, P(X = 2000) = 0.3, P(X = 2500) = 0.3, P(X = 3000) = 0.1 is not practical as a distribution for the number of phone calls to a help-desk call center during a day
Homework Answers
as number of phone calls to a help-desk call center during a day can take any values from set {0,1,2,3,4......}
therfore its pmf should be defined for all these values while above pmf has been distributed for only 1000,1500,2000,2500 and 3000 number of calls ; which means there will only this number of calls will arrive and nothing else which can not be possible
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Explain why the probability mass function P(X = 1000) = 0.1, P(X
= 1500) = 0.2,...
A discrete random variable X has probability mass function P() 0.1 0.2 0.2 0.2 0.3 Use...
A discrete random variable X has probability mass function P() 0.1 0.2 0.2 0.2 0.3 Use the inverse transform method to generate a random sample of size from the distribution of X. Construct a relative frequency table and compare the empirical with the theoretical probabilities. Repeat using the R sample function. 1000
Calculate P(0.2<=X<=0.4) for the following discrete probability mass function: X = {0.1, 0.2, 0.3, 0.4} and...
Calculate P(0.2<=X<=0.4) for the following discrete probability mass function: X = {0.1, 0.2, 0.3, 0.4} and f(x) = {0.29, 0.15, 0.35, 0.21}
2) Consider a random variable with the following probability distribution: P(X = 0) = 0.1, P(X=1) =0.2, P(X=2) = 0.3, P(X=3) = 0.3, and P(X=4)= 0.1. A. Generate 400 values of this random variable with...
2) Consider a random variable with the following probability distribution: P(X = 0) = 0.1, P(X=1) =0.2, P(X=2) = 0.3, P(X=3) = 0.3, and P(X=4)= 0.1. A. Generate 400 values of this random variable with the given probability distribution using simulation. B. Compare the distribution of simulated values to the given probability distribution. Is the simulated distribution indicative of the given probability distribution? Explain why or why not. C. Compute the mean and standard deviation of the distribution of simulated...
Complete the following probability distribution table: Probability Distribution Table X P(X) 10 33 0.2 37 0.1...
Complete the following probability distribution table: Probability Distribution Table X P(X) 10 33 0.2 37 0.1 49 0.3
1. Which of the following is a probability mass function for some probability distribution p with...
1. Which of the following is a probability mass function for some probability distribution p with domain {1,2,3,4}? P(1)=0.1,P(2)=0.2,P(3)=0.3,P(4)=0.4 P(1)=0.1,P(2)=0.1,P(3)=0.3,P(4)=0.4 P(1)=0.2,P(2)=0.4,P(3)=0.3,P(4)=0.4 P(1)=-0.5,P(2)=0.8,P(3)=0.5,P(4)=0.2 2. Let X be the random variable where X is the number of heads after flipping a fair coin 50 times. What is the mean of X? 3. Suppose that one flips a fair coin 6 times. What is the probability of getting at most 2 heads? 4. Which of the following is a discrete probability distribution and...
Consider the following probability distribution: x P(x) 1 0.1 2 ? 3 0.2 4 0.3 What...
Consider the following probability distribution: x P(x) 1 0.1 2 ? 3 0.2 4 0.3 What must be the value of P(2) if the distribution is valid? A. 0.6 B. 0.5 C. 0.4 D. 0.2 What is the mean of the probability distribution? A. 2.5 B. 2.7 C. 2.0 D. 2.9
2. Consider a random variable with the following probability distribution: P(X=0) = 0.1, P(X=1) = 0.2,...
2. Consider a random variable with the following probability distribution: P(X=0) = 0.1, P(X=1) = 0.2, P(X=2) = 0.4, and P(X=3) = 0.3 a. Find P(X<=1) b. Find P(1<X<=3)
Consider the probability distribution shown below: X 10 12 18 20 p(x) 0.2 0.3 0.1 0.4...
Consider the probability distribution shown below: X 10 12 18 20 p(x) 0.2 0.3 0.1 0.4 Find the standard deviation of X.
The gross payoffs (X) from the investment have the following probability mass function. x p(x) 0...
The gross payoffs (X) from the investment have the following probability mass function. x p(x) 0 0.5 2000 0.2 5000 0.3 The expected gross payoff (mean payoff) is:...............
5.Consider a discrete random variable X with the probability mass function xp(x) Consider Y-g(X) 0.2 0.4...
5.Consider a discrete random variable X with the probability mass function xp(x) Consider Y-g(X) 0.2 0.4 0.3 0.1 a)Find the probability distribution of Y b) Find the expected value of Y, E(Y) Does μ Y equal to g(μx)? 4
A discrete random variable X has probability mass function P() 0.1 0.2 0.2 0.2 0.3 Use the inverse transform method to generate a random sample of size from the distribution of X. Construct a relative frequency table and compare the empirical with the theoretical probabilities. Repeat using the R sample function. 1000
5.Consider a discrete random variable X with the probability mass function xp(x) Consider Y-g(X) 0.2 0.4 0.3 0.1 a)Find the probability distribution of Y b) Find the expected value of Y, E(Y) Does μ Y equal to g(μx)? 4
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