I think using a ratio between 5%ci and the 95%ci to determine if something is normal, might be incorrect for any highly variable dataset. What if we used the absolute difference from the ci to the mean.
log normal distribution should have a longer right tail, so this should work. So if the abs(95ci—mean) is a lot larger than the abs(5%ci—mean) then you could take an initial guess it is lognormal. If the ratio is around 1, you might have normal data.
Like you said, this is still just a quick and imperfect check.
This post is great.
I think using a ratio between 5%ci and the 95%ci to determine if something is normal, might be incorrect for any highly variable dataset. What if we used the absolute difference from the ci to the mean.
log normal distribution should have a longer right tail, so this should work. So if the abs(95ci—mean) is a lot larger than the abs(5%ci—mean) then you could take an initial guess it is lognormal. If the ratio is around 1, you might have normal data.
Like you said, this is still just a quick and imperfect check.