Amanufacturer produces trinkets targeted to weigh 52 g. the weight of the trinkets is known to be normally distributed, but an engineer is concerned that the variation in the produced trinkets is larger than acceptable. in an attempt to estimate the variance, she selects n = 10 trinkets at random and weighs them. the sample yields a sample variance of 4 g2. define 90% ci for the variance.

Asample of 200 rom computer chips was selected on each of 30 consecutive days, and the number of nonconforming chips on each day was as follows: the data has been given so that it can be copied into r as a vector. non.conforming = c(10, 15, 21, 19, 34, 16, 5, 24, 8, 21, 32, 14, 14, 19, 18, 20, 12, 23, 10, 19, 20, 18, 13, 26, 33, 14, 12, 21, 12, 27) #construct a p chart by using the following code. you will need to enter your values for pbar, lcl and ucl. pbar = lcl = ucl = plot(non.conforming/200, ylim = c(0,.5)) abline(h = pbar, lty = 2) abline(h = lcl, lty = 3) abline(h = ucl, lty = 3)