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A truck manufacturer monitors the width of the door seam as vehicles come off its assembly line. the seam width is the distance between the edge of the door and the truck body, in inches. these data are 62 days of measurements of a passenger door seam, with 10 trucks measured each day. it has been claimed that the process has an average width of 0.275 inches with sigma =.01.
A) if the seam widths at this assembly line are normally distributed, then what is the probability of finding a seam wider than 1/2 inch.
B) if the process is under control, what is the probability of finding the mean of a daily sample of 10 widths more than 3 standard errors away from the population average of 0.275?
Twenty-six observations are used to obtain the following regression results: DEPENDENT VARIABLE: LNY R-SQUARE F-RATIO P-VALUE ON F OBSERVATIONS: 26 0.3647 4.21 0.0170 VARIABLE PARAMETER STANDARD ESTIMATE ERROR T-RATIO P-VALUE INTERCEPT 2.9957 0.3545 ..
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