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Please post rest question again .
if you can answer any of these i’d would appreciate it greatly 1. List the reasons...
Suppose that X is continuous random variable with 2. 1 € [0, 1] probability density function fx(2) = . Compute the 10 ¢ [0, 1]" following: (a) The expectation E[X]. (b) The variance Var[X]. (c) The cumulative distribution function Fx.
Appreciate if you can answer this ONE QUESTION COMPLETELY and give me a detailed working with explanation for me to understand. Once completed so long as my doubts are cleared and the solutions are correct, I will definitely vote up. Some of the question are similiar to take a look carefully before you answer as it's very important for me. Thank you Question 1 A laboratory test is 95 % correct in detecting a certain disease when the disease is...
Appreciate if you can answer this ONE QUESTION COMPLETELY and give me a detailed working with explanation for me to understand. Once completed so long as my doubts are cleared and the solutions are correct, I will definitely vote up. Some of the question are similiar to take a look carefully before you answer as it's very important for me. Thank you Question 2 (a) Identify the mean and variance of a standard normal random variable Z. Determine the following...
Appreciate if you can answer this ONE QUESTION COMPLETELY and give me a detailed working with explanation for me to understand. Once completed so long as my doubts are cleared and the solutions are correct, I will definitely vote up. Some of the question are similiar to take a look carefully before you answer as it's very important for me. Thank you. Question 4 (a) Suppose that the length of time t (in days) between sales for an automobile salesperson...
This is for a C# program. I would greatly appreciate any help! Thank you:) For this assignment you're going to create a console application called A02PBallGenerator. This app is going to mimic a quick pick program in a lotto terminal. When the user runs your app you're going to select the numbers for them. Then you'll ask them if they'd like another set of numbers. Y for yes and N for No Use a do while loop so that if...
The random variable X takes the values -2, -1 and 3 according to the following probability distribution: -2 3k -1 2k 3 3k px(x) i. Explain why k = 0.125 and write down the probability distribution of X. ii. Find E(X), the expected value of X. iii. Find Var(X), the variance of X.
2) Consider a random variable with the following probability distribution: P(X-0)-0., Px-1)-0.2, PX-2)-0.3, PX-3) -0.3, and PX-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 values. How do these summary measures compare to the...
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...
I have two questions I'm having trouble understanding. I greatly appreciate any help you all can give me! I'm not great at physics so the more details the better. THANKS!!! In the RC circuit of Figure WG32.6, the emf of the AC source is given by 'E = Emax sin ω| t. The emf amplitude is Emax = 10 V, and the angular frequency is ω,-100 s-1 when the angular frequency is changed to a new value ω2, the time...
Please show all work so I can learn <3 XOXO I would appreciate it alot ;) 1 Random Variables Consider the probability space (2, A, P) defined as follows: .A-2. i.e., the event space is the power set of Ω; P(R)1/3, P(G) P(B) PY-2/9, where we define the probability only for the clementary outcomes, and the probability of every event in A can be deduced from these valucs (as per discussion in section A.5) This probability space can model, for...