My dog just had 3 frisky puppies who jump in and outof their whelping box. A puppy spends an average of 10minutes (exponentially distributed) in the whelping boxbefore jumping out. Once out of the box, a puppy spends anaverage of 15 minutes (exponentially distributed) beforejumping back into the box.a At any given time, what is the probability that morepuppies will be out of the box than will be in the box? b On the average, how many puppies will be in thebox?
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!
My dog just had 3 frisky puppies who jump in and out
of their whelping box. A puppy spends an average of 10
minutes (exponentially distributed) in the whelping box
before jumping out. Once out of the box, a puppy spends an
average of 15 minutes (exponentially distributed) before
jumping back into the box.
a At any given time, what is the probability that more
puppies will be out of the box than will be in the box?
b On the average, how many puppies will be in the
box?
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