MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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- A continuous random variable X has a uniform distribution on the interval [-3, 3]. Sketch the graph of its density function.arrow_forwardPlease answer number 3arrow_forwardSuppose that X and X, have joint probability density function x2, if 1< xı < 2 and 1 < r2 < 3 10, fx1.x.("1, 2) = otherwise. What is the joint probability density function fy,y, of Y1 = X1/X2 and Y, = X2?arrow_forward
- 11. Let X be a continuous random variable with probability density function r>0 f(x)= 0, otherwise, where 1> 0. Let Y be the largest integer less than or equal to X. Determine the probability function of Y.arrow_forwardHi. Please help. I need to calculate the mean and vairance of the probabiltiy density function I am getting one minute but the time better each serving is at least 2 minutes. Can you correct me as I have gone wrong somewhere. (see attached doc)arrow_forwardA number x is selected at random from [4, 20]. The probability density function for x is given by f(x) = for 4 ≤ x ≤ 20. 2 Find the probability that a number selected is in the sub-interval [7, 18].arrow_forward
- Please answer number 4arrow_forwardLet X be a random variable that follows the beta distribution. This random variable is continuous and is defined over the interval from 0 to 1. The probability density function is given by whereand are integers, whose values determine the shape of the probability density function. Because X varies between 0 and 1, we can think of X as the probability that some event (say) E occurs or the proportion of times an event occurs in some population. For example, E could denote the event that a critical part in a newly designed car will lead to a catastrophic failure in accidents at high speeds. The expected value (i.e., mean) of this random variable is []. That is, . The Excel commands for the beta random variable are =beta.dist(x,,,true,0,1) for the cumulative probability distribution, and =beta.dist(x,,,false,0,1) for the probability density function. (a) Now, think in Bayesian terms.…arrow_forward
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