Skewed distribution

Some possibilities:
a) your assumption that it should be distributed normally, was wrong.
b) a rare instance of chance variation; even with n=30, some samples from a normally distributed population can be skewed.
c) the influence of an unanticipated second factor.
Thank you for the quick reply.

a) In a stable production process with millions of parts passing through, for example drilling the same hole. If I take a random sample, shouldnt it be normally distributed?
A sample of n=30 is never perfectly normally distributed, even if the underlying distribution is normal.
Most of the time, the samples will a show a distribution quite close to a normal distribution. But due to
chance, a certain proportion of samples will look different.


Less is more. Stay pure. Stay poor.
Do you have historic data to compare it too?

Can you post the data in a histogram?

What is the actual outcome variable (e.g., time, size, etc.)?

Have you put precision bounds on it to show that it is outside an expected range for a stable process?

@Miner please help direct them on how to do this or given any relevant advice!