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Stats III: Non-normality
- Moments
- Skewness
- Kurtosis
- An example
- The lognormal distribution
- Calculating probabilities again
- The big picture
- Excel section
We concluded the previous chapter with a word of caution, stressing that normality is a convenient assumption that may or may not describe properly the distribution of the variable we want to analyze. We now move on to discuss a few issues related to non-normal distributions, with a focus on the lognormal distribution.
Moments
All distributions, normal and non-normal, are characterized by parameters called moments. The first two moments we already know: The mean and the variance. For a normal distribution, that is all that matters. Remember, once we know the mean and variance of a normal ...
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