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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 10 ounces. a. The process standard deviation is 0.15, and the process control is set at plus or minus one standard deviation. Units with weights less than 9.85 or greater than 10.15 ounces will be classified as defects. What is the probability of a defect (to 4 decimals)? In a production run of 1,000 parts, how many defects would be found (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 9.85 or greater than 10.15 ounces being classified as defects. What is the probability of a defect (to 4 decimals)? In a production run of 1,000 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 10 ounces. a. The process standard deviation is 0.15, and the process control is set at plus or minus one standard deviation. Units with weights less than 9.85 or greater than 10.15 ounces will be classified as defects. What is the probability of a defect (to 4 decimals)? In a production run of 1,000 parts, how many defects would be found (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 9.85 or greater than 10.15 ounces being classified as defects. What is the probability of a defect (to 4 decimals)? In a production run of 1,000 parts, how many defects would be found (to the nearest whole number)?

MATLAB: An Introduction with Applications
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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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 10 ounces. a. The process standard deviation is 0.15, and the process control is set at plus or minus one standard deviation. Units with weights less than 9.85 or greater than 10.15 ounces will be classified as defects. What is the probability of a defect (to 4 decimals)? In a production run of 1,000 parts, how many defects would be found (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 9.85 or greater than 10.15 ounces being classified as defects. What is the probability of a defect (to 4 decimals)? In a production run of 1,000 parts, how many defects would be found (to the nearest whole number)?
Transcribed Image Text: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 10 ounces. a. The process standard deviation is 0.15, and the process control is set at plus or minus one standard deviation. Units with weights less than 9.85 or greater than 10.15 ounces will be classified as defects. What is the probability of a defect (to 4 decimals)? In a production run of 1,000 parts, how many defects would be found (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 9.85 or greater than 10.15 ounces being classified as defects. What is the probability of a defect (to 4 decimals)? In a production run of 1,000 parts, how many defects would be found (to the nearest whole number)?
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