Theoretical Exercises in Probability and Statistics, 2nd by Najeeb Abdur Rahman

By Najeeb Abdur Rahman

Those routines are designed to teach the facility and makes use of of likelihood and statistical tools. Over 550 difficulties illustrate purposes in arithmetic, economics, undefined, biology, and physics. solutions are integrated for these operating the issues on their lonesome.

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Theoretical Exercises in Probability and Statistics, 2nd Edition

Those routines are designed to teach the ability and makes use of of likelihood and statistical tools. Over 550 difficulties illustrate functions in arithmetic, economics, undefined, biology, and physics. solutions are incorporated for these operating the issues on their lonesome.

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38 For a random variable X having a unit normal distribution prove that 1 00 (_1)'x2r+l (x > 0). + ~. r . --. x r I 2r r=1 where Verify that this series expansion for the distribution function of X is asymp· totic by proving that, for any n, the remainder is less in absolute value than the last term taken into account. ~-. 1+ 2' 2, " y 2n x ,= 1 • X • r . 1 (x 2 + 2k). 40 A random variable X has the probability density function J(X = x) = ksin 2n xcosx defined in the range (-nI2 ::; X ::; nI2), where k is a function of the positive integer II.

99 In a game of skill, a trial can result in anyone of m mutually exclusive results R l' R 2 , ••• , Rm· The probability for Ry to happen is proportional to p", where p is a constant (0 < p < t). The stake for each trial is one shilling, and if Ry occurs at a trial the player receives AV shillings, where (0 < A< 1). If S. denotes the amount received by a player after n independent trials, prove that the probability-generating function of S. is _ [(1- p)8'<{ 1- (POl)m}]. G(O) - (1- pIH)(1- pO") .

For X the joint probability density function proportional to = x. Y = Y. )a defined in the range (0 ~ Y < 00; - 00 < X < (0). where ex is a parameter > 3 Determine the proportionality factor and the marginal distribution of X. He~ce calculate the mean and variance of X. Also, show that the distribution function of Y is J 00 e-YXl P(Y ~ y) = l-(ex-l) o dx I ( +x)" • and verify that all the moments of Y diverge. Use these results to prove that X and Yare uncorrelated but not independently distributed random variables.

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