Applied Statistics and Probability for Engineers
4-7 NORMAL APPROXIMATION TO THE BINOMIAL AND POISSON DISTRIBUTIONS 119 EXAMPLE 4-17 In a digital communication channel, assume t ...
120 CHAPTER 4 CONTINUOUS RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS EXAMPLE 4-18 The digital communication problem in the pr ...
4-7 NORMAL APPROXIMATION TO THE BIOMIAL AND POISSON DISTRIBUTIONS 121 Recall that the binomial distribution is a satisfactory ap ...
122 CHAPTER 4 CONTINUOUS RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS 4-63. The manufacturing of semiconductor chips produces ...
4-9 EXPONENTIAL DISTRIBUTION 123 Therefore, is the cumulative distribution function of X. By differentiating F(x), the probabili ...
124 CHAPTER 4 CONTINUOUS RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS Also, the cumulative distribution function can be used t ...
4-9 EXPONENTIAL DISTRIBUTION 125 Furthermore, the mean time until the next log-on is The standard deviation of the time until th ...
126 CHAPTER 4 CONTINUOUS RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS and Therefore, After waiting for 3 minutes without a det ...
4-9 EXPONENTIAL DISTRIBUTION 127 memory property of the exponential distribution implies that the device does not wear out. That ...
128 CHAPTER 4 CONTINUOUS RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS (b) Determine xsuch that the probability that you wait l ...
4-10 ERLANG AND GAMMA DISTRIBUTIONS 129 occur in a Poisson process. The random variable that equals the interval length until rc ...
130 CHAPTER 4 CONTINUOUS RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS EXAMPLE 4-24 An alternative approach to computing the pr ...
4-10 ERLANG AND GAMMA DISTRIBUTIONS 131 It can be shown that the integral in the definition of is finite. Furthermore, by using ...
132 CHAPTER 4 CONTINUOUS RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS the gamma distribution in which and requals one of the v ...
4-11 WEIBULL DISTRIBUTION 133 (c) The error-correcting code might be ineffective if there are three or more errors within bits. ...
Also, the following result can be obtained. 134 CHAPTER 4 CONTINUOUS RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS If Xhas a We ...
4-12 LOGNORMAL DISTRIBUTION 135 4-109. Suppose that X has a Weibull distribution with and hours. Determine the mean and vari- an ...
136 CHAPTER 4 CONTINUOUS RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS The parameters of a lognormal distribution are and , but ...
4-12 LOGNORMAL DISTRIBUTION 137 What lifetime is exceeded by 99% of lasers? The question is to determine xsuch that . Therefore, ...
138 CHAPTER 4 CONTINUOUS RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS 4-127. The time between calls is exponentially distribut ...
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