Hi all,
I've got a question about distributions, it might require a philosophical
answer, what makes particular distributions of interest (e.g. the normal,
chi-square, etc.) How did statisticians discover these distributions and why
did they think that they are of importance?

Second question: I cannot grasp the practical implications or meaning of
normality in a data set, when is it ok to assume normality and why not
assume something else, for example, in linear regression when it is assumed
that the errors are normal... what does that really mean graphically, does
it mean that plotting the errors in the sample we have will show as a normal
curve???

Third question: When we assume that the variance is constant, say the error
term in linear regression, does that mean that the error term for each data
point is equally dispersed around the fitted curve?

I know some question might not be phrased properly but any help or
corrections with these questions will be highly appreciated.
Fahd



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