The life of a semiconductor laser at a constant power is normally distributed with a mean of 7500 hours and a standard deviation of 500 hours. a. What is the probability that a laser fails before 5500 hours? b. What is the probability that a laser lasts more than 8250 hours? c. What is the life in hours that 95% of the lasers exceed?
The life of a semiconductor laser at a constant power is normally distributed with a mean of 7500 hours and a standard deviation of 500 hours. a. What is the probability that a laser fails before 5500 hours? b. What is the probability that a laser lasts more than 8250 hours? c. What is the life in hours that 95% of the lasers exceed?
The life of a semiconductor laser at a constant power is normally distributed with a mean of 7500 hours and a standard deviation of 500 hours. a. What is the probability that a laser fails before 5500 hours? b. What is the probability that a laser lasts more than 8250 hours? c. What is the life in hours that 95% of the lasers exceed?
The life of a semiconductor laser at a constant power is normally distributed with a mean of 7500 hours and a standard deviation of 500 hours. a. What is the probability that a laser fails before 5500 hours?
b. What is the probability that a laser lasts more than 8250 hours? c. What is the life in hours that 95% of the lasers exceed?
Transcribed Image Text:Q2: The life of a semiconductor laser at a constant power is normally distributed with
a mean of 7500 hours and a standard deviation of 500 hours.
a. What is the probability that a laser fails before 5500 hours?
b. What is the probability that a laser lasts more than 8250 hours?
c. What is the life in hours that 95% of the lasers exceed?
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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