A machining operation produces bearings with diameters that are normally distributed with a mean of 3.0005 inches and a standard deviation of .0010 inches. Specifications require the bearing diameters to lie in the interval of 3.000 +/-.0020 inches. Those outside the interval are considered scrap and must be disposed of. With the existing machine setting, what fraction of total production will be scrap
A machining operation produces bearings with diameters that are normally distributed with a mean of 3.0005 inches and a standard deviation of .0010 inches. Specifications require the bearing diameters to lie in the interval of 3.000 +/-.0020 inches. Those outside the interval are considered scrap and must be disposed of. With the existing machine setting, what fraction of total production will be scrap
A machining operation produces bearings with diameters that are normally distributed with a mean of 3.0005 inches and a standard deviation of .0010 inches. Specifications require the bearing diameters to lie in the interval of 3.000 +/-.0020 inches. Those outside the interval are considered scrap and must be disposed of. With the existing machine setting, what fraction of total production will be scrap
A machining operation produces bearings with diameters that are normally distributed with a mean of 3.0005 inches and a standard deviation of .0010 inches. Specifications require the bearing diameters to lie in the interval of 3.000 +/-.0020 inches. Those outside the interval are considered scrap and must be disposed of. With the existing machine setting, what fraction of total production will be scrap?
Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.
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