Consider again problem 3 of Sect. 4.1 and the data given there. A painting process was investigated and determined to be stable with an approximately normal distribution. The variable of interest was paint thickness. Acceptable paint thicknesses are between 4 and 6 units. (a) Using the sample standard deviation from the data, give a 90 % confidence interval for 6σ,where σ is the standard deviation of paint thickness from all items (at the specified location on the items). (b) Using the standard deviation and sample average from the data, would the current painting process be considered “acceptable” or of high quality? Why?
Consider again problem 3 of Sect. 4.1 and the data given there. A painting process was investigated and determined to be stable with an approximately
(a) Using the sample standard deviation from the data, give a 90 % confidence interval for 6σ,where σ is the standard deviation of paint thickness from all items (at the specified location on the items).
(b) Using the standard deviation and sample average from the data, would the current painting process be considered “acceptable” or of high quality? Why?
Problem 3
A painting process was studied and determined to be stable. The variable of interest was paint thickness on a particular item at a specified location on the item. The following paint thickness data were recorded for n = 10 such items in some unspecified units.
(a) Make a normal probability plot for the data. Does it appear that a normal model for paint thickness is adequate? Why or why not?
(b) Make a box plot of the data. Do you find any outliers?
(c) Based on the normal probability plot, (graphically) estimate the 1st quartile, the 3rd quartile, and the median of paint thicknesses.
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