Example 5-17. The elementary probability law of a continuous r.v. is:f(x) = yoe-a), asxS0, b> 0, where a, b and y, are constants.Show that y, = b = 1/o and a = m - o, where m and o are respectively the mean andstandard deviation of the distribution. Show also that B, =4 and B, = 9.%3D%3D

Answered: Image /qna-images/answer/9569e2b7-98fb-4b36-9dd2-f1488767d8ef.jpg

Answered: Example 5-17. The elementary…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Question 8 Suppose that X ~ B(9, 0.3). Find the following probabilities. Round to three decimals. a. P(X = 5): b. P(X 5): Submit Question MacBook Ai
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JUR 1. Suppose the lifetime of a particular brand of light bulbs is exponentially distributed with a mean of 400 hours. a) Find the probability that a randomly selected light bulb would last over 500 hours. b) Find the probability that a randomly selected light bulb would last under 300 hours. lu colected light bulbs would last over 500 67
The distribution function for a random variable X is F (x) = {-e-", 20 x > 0 to x 2? e 2 e -5 -4 e
A shipment of 7 television sets contains 2 defective sets. A hotel makes a random purchase of 3 of the sets. If X is the number of defective sets purchased by the hotel, (a) find the probability distribution of X, express it in a table format. Probability distribution of X X P(X) (b) Find the cdf of X. (c) Find the E(X) and Var(X)
A technician suspect that the number of computer errors recorded per day in the LAN follows a Poisson distribution with a mean of 2 errors per day. Record of the number of errors per day for the past 260 days are shown in table below. Number of Number of Pr(X = x) E (0; – e;) Errors per days ei day 77 1 90 2 55 3 30 4 or more a. Test the hypothesis that the number of computer errors per day has the Poisson distribution with mean 2 at the 5% significance level. b. Find an approximate value of the p – value for the test statistics in (a). 8
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The table gives the joint probability distribution of the number of sports an individual plays (X) and the number of times she may get injured while playing (Y) X=1 X=2 X=3 0.12 0.08 0.15 0.06 0.05 0.05 0.10 0.03 0.15 0.15 0.04 0.02 Y=4 Y=3 Y=2 Y=1 The covariance between X and Y, oxy, is (Round your answer to two decimal places Enter a minus sign if your answer is negative) The correlation between X and Y, corr(X, Y), is (Round your answer to two decimal places Enter a minus sign if your answer is negative.) An increase in the number of sports an individual plays will tend to * the number of times she may got injured while playing
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Example 5-17. The elementary probability law of a continilolS f(x) = yoe-), asxS0, b>0, where a, b and y, are constants. Show that y, = b = 1/o and a = m – 0, where m and o are respectively the mean and standard deviation of the distribution. Show also that B, = 4 and B, = 9. %3D %3! %3D