An average of 1 package is sent to a server in 1 second. The server, on the other hand, uses the 5 packages that come to it. is preparing a document. The time between packets is modeled as an exponential random variable. X of the server Let it be a random variable expressing the time it takes to prepare a document. Passing for the preparation of a document your time a. Find the probability that it is more than 10 seconds. b. Find the probability that it is between 5 seconds and 10 seconds.
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
An average of 1 package is sent to a server in 1 second. The server, on the other hand, uses the 5 packages that come to it.
is preparing a document. The time between packets is modeled as an exponential random variable. X of the server
Let it be a random variable expressing the time it takes to prepare a document. Passing for the preparation of a document
your time
a. Find the probability that it is more than 10 seconds.
b. Find the probability that it is between 5 seconds and 10 seconds.
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