
A common tool for comparing if two populations are the same is the “student t-test.” This is often used in reliability, and science, if we want to investigate if a factor has caused a change in a respnse.
A population was assembled in location “A”. Another population was assembled in location “B”. Population “A” has an average defect rate of 4%. Population “B” has an average defect rate of 5.5%. Does the location of assembly affect defect rate? That’s just a big argument unless we can project the statistical likelihood that what we have measured is not just an overlap of noise. [Read more…]