The observed annual maximum runoff, X, in the Kızılırmak River has been modelled by a normal distribution with parameters, µx=256.7 m³/sec and ox = 191 m³/sec. %3D a) Compute the probability that X > 400 m³/sec according to the normal distribution model. b) If X is now assumed to be lognormally distributed, find the parameters of this lognormal distribution and again compute the probability that X > 400 m³/sec according to the lognormal model. c) Compare the probabilities you have computed according to this two models. Why are the results different? Comment.
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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