Motorola used the normal distribution to determine the probability of defects and the number of defects expected in a production process. Assume a production process produces items with a mean weight of 6 ounces.**a.** The process standard deviation is 0.10, and the process control is set at plus or minus 1.5 standard deviation \( s \). Units with weights less than 5.85 or greater than 6.15 ounces will be classified as defects. What is the probability of a defect (to 4 decimals)?[Input Box]**In a production run of 1000 parts, how many defects would be found (round to the nearest whole number)?**[Input Box]**b.** Through process design improvements, the process standard deviation can be reduced to 0.05. Assume the process control remains the same with weights less than 5.85 or greater than 6.15 ounces being classified as defects. What is the probability of a defect (round to 4 decimals; if necessary)?[Input Box]**In a production run of 1000 parts, how many defects would be found (to the nearest whole number)?**[Input Box]**c.** What is the advantage of reducing process variation, thereby causing a problem to be at a greater number of standard deviations from the mean?[Input Box: It can substantially reduce the number of defects]

Refer Standard normal table/Z-table OR use excel formula "=NORM.S.DIST(-1.5, TRUE)" &…

Motorola used the normal distribution to determine the probability of defects and the number of defects expected in a production process. Assume a production process produces items with a mean weight of 6 ounces. a. The process standard deviation is 0.10, and the process control is set at plus or minus 1.5 standard deviation s. Units with weights less than 5.85 or greater than 6.15 ounces will be classified as defects. What is the probability of a defect (to 4 decimals)? In a production run of 1000 parts, how many defects would be found (round to the nearest whole number)? b. Through process design improvements, the process standard deviation can be reduced to 0.05. Assume the process control remains the same with weights less than 5.85 or greater than 6.15 ounces being classified as defects. What is the probability of a defect (round to 4 decimals; if necessary)? In a production run of 1000 parts, how many defects would be found (to the nearest whole number)?

Motorola used the normal distribution to determine the probability of defects and the number of defects expected in a production process. Assume a production process produces items with a mean weight of 6 ounces. a. The process standard deviation is 0.10, and the process control is set at plus or minus 1.5 standard deviation s. Units with weights less than 5.85 or greater than 6.15 ounces will be classified as defects. What is the probability of a defect (to 4 decimals)? In a production run of 1000 parts, how many defects would be found (round to the nearest whole number)? b. Through process design improvements, the process standard deviation can be reduced to 0.05. Assume the process control remains the same with weights less than 5.85 or greater than 6.15 ounces being classified as defects. What is the probability of a defect (round to 4 decimals; if necessary)? In a production run of 1000 parts, how many defects would be found (to the nearest whole number)?

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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