Chapter 8: Q.8.3 (page 393)
If
give an upper bound to
(a)
(b)
(c);
Short Answer
An upper bound to
(a).
(b).
(c).
Chapter 8: Q.8.3 (page 393)
If
give an upper bound to
(a)
(b)
(c);
An upper bound to
(a).
(b).
(c).
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Get started for freeItis a Poisson random variable with a mean, thenis approximately
or
Explain why a gamma random variable with parametershas an approximately normal distribution whenis large.
Let be a sequence of independent and identically distributed random variables with distribution, having a finite mean and variance. Whereas the central limit theorem states that the distribution ofapproaches a normal distribution as goes to infinity, it gives us no information about how largeneed to be before the normal becomes a good approximation. Whereas in most applications, the approximation yields good results whenever, and oftentimes for much smaller values of, how large a value of is needed depends on the distribution of. Give an example of distribution such that the distributionis not close to a normal distribution.
Hint: Think Poisson.
8.5 The amount of time that a certain type of component functions before failing is a random variable with probability density function
Once the component fails, it is immediately replaced by
another one of the same type. If we let denote the life-time of the th component to be put in use, then represents the time of the th failure. The long-term rate at which failures occur, call it, is defined by
Assuming that the random variables are independent, determine .
It is a gamma random variable with parameters, approximately how large must be so that
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