Why is log curve of a variable better fit for normal distribution?
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In probability theory, a log-normal (or lognormal) distribution is a continuous probability distribution of a random variablewhose logarithm is normally distributed. Thus, if the random variable X is log-normally distributed, then Y = ln(X) has a normal distribution. Likewise, if Y has a normal distribution, then the exponential function of Y, X = exp(Y), has a log-normal distribution. A random variable which is log-normally distributed takes only positive real values.
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