Continuing the previous problem, one of the leading quality gurus, Genichi Taguchi of Japan, suggested the idea of a quadratic loss function when judging quality. Rather than saying that a part is "good" when its measurement falls within specification limits and is "bad" otherwise, the quadratic loss function estimates the part's quality as (x - T)2 , where x is the part's measurement and T is the target measurement.
a. Using this loss function, estimate the average quality of parts from process 1, given the data in the file P20_66.xlsx and a target of 10.50 inches. Do the same for process
2. Which process appears to be better?
b. Explain intuitively why a quadratic loss function might be preferable to a simple 0 - 1 function (where a part either meets specifications or it doesn't) when assessing quality.