You decide to play K number of video games, where K is a Poisson random variable with parameter A. Assume that time you spend on a video game k = 1, 2, ..., K has a normal distribution with mean µk and variance o. Also assume that Hk >> 0 and ož is small, so that you can neglect negative time values. Let T be the total time you spend on playing video games, compute the mean and variance of T. %3D
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!
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