ccording to the Huffington Post2, internet users are see about 11,250 online advertisements per month. Suppose that this is a normal random variable and that its standard deviation is 3,300 online advertisements per month. 1.)How few ads would a person have to be exposed to on a monthly basis such that the probability of seeing this few number of ads or less is only 10%? 2.) What’s the probability of seeing more than 20,000 ads per month? 3.) What’s the probability that the number of monthly ads someone will see is within three standard deviations of the mean?
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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