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- Please answer both7.2.3. X is the continuous uniform (-5, 5) random variable. Given the event B = {|X| < 3}, find the (a) conditional PDF, fx|B(x), (b) conditional expected value, E[X|B], (c) conditional variance, Var[X|B].2. For the following discrete variable with probability f(x) X 1 3 4 5 f(x) 0.2 0.15 2c 0.05 0.15 (a) Determine the value of c Select one: О а. 0.15 O b. 0.225 0.25 O c. none O d. 0.4
- Current Attempt in Progress 3(8x – x²) Suppose that f(x) = - for 0 2) = i (e) Determine x such that P(X < x) = 0.75. X = iFor RBD topology 1, the independent component working probabilities are P(A)0.83, P(B)-0.73, PIC)0.45, PID0.66, P(E0.83. What is the probability that the system will work? Your answer: O 0.382043 O 0.520173 O 0,436623 O 0.929271 O 0.903641 O 0.152346 O 0,952901 O 0728327Find the following probabilities; P(0<z<2.32)
- A branch of a certain bank has six ATMs. Let X represent the number of machines in use at a particular time of day. The cdf of X is as follows: F(x) = (b) Calculate the following probabilities directly from the cdf: (a) p(2), that is, P(X = 2) (c) 0 0.09 0.21 0.33 0.53 0.90 0.99 1 P(X > 3) x < 0 0 < x < 1 1 ≤ x < 2 2Calculate the following probabilities in two decimal places: (a) Y is distributed x 1. Then, Pr( Y>9.49) = (b) Y is distributed to. Then, Pr( Y> -0.5) = (c) Y is distributed F4,- Then, Pr( Y 696 or Y<304) =Example 2.14. Show the CDF of the random variable X with the following pdf: Sx(2) = lwa(x) Example 2.15. Let X be a random variable with the following pdf: 1. Find its CDF. 2. Evaluate the following probabilities using its CDF and/or pdf. a) P(} 1) c) P(X > }|X < 1)Event A is my wife cooking dinner tonight. It has been determined that P(A) = 0.15. What is P(not A)?I need help with this question.Example 3.6.4 Let X have the N(10, 16) distribution (ie. Ganssian distribution with mean 10 and variance 16). Find the munerical values of the following probabilities: P{X 2 15), PEX <5), P{X² 2400), and P{X = 2}.