he thicknesses of glass sheets produced by a certain process are normally distributed with a mean of μ =3.50 mm and a standard deviation of σ = 0.15 mm. a) What is the probability that a glass sheet is thicker than 3.75 mm? b) What is the probability that a glass sheet is thinner than 3.30 mm? c) What is the probability that a glass sheet is between 3.25mm and 3.75mm? d) What is the value of c for which there is a 99% probability that a glass sheet has a thickness within the interval [3.50 − c, 3.50 + c]?
he thicknesses of glass sheets produced by a certain process are normally distributed with a mean of μ =3.50 mm and a standard deviation of σ = 0.15 mm. a) What is the probability that a glass sheet is thicker than 3.75 mm? b) What is the probability that a glass sheet is thinner than 3.30 mm? c) What is the probability that a glass sheet is between 3.25mm and 3.75mm? d) What is the value of c for which there is a 99% probability that a glass sheet has a thickness within the interval [3.50 − c, 3.50 + c]?
he thicknesses of glass sheets produced by a certain process are normally distributed with a mean of μ =3.50 mm and a standard deviation of σ = 0.15 mm. a) What is the probability that a glass sheet is thicker than 3.75 mm? b) What is the probability that a glass sheet is thinner than 3.30 mm? c) What is the probability that a glass sheet is between 3.25mm and 3.75mm? d) What is the value of c for which there is a 99% probability that a glass sheet has a thickness within the interval [3.50 − c, 3.50 + c]?
The thicknesses of glass sheets produced by a certain process are normally distributed with a mean of μ =3.50 mm and a standard deviation of σ = 0.15 mm. a) What is the probability that a glass sheet is thicker than 3.75 mm? b) What is the probability that a glass sheet is thinner than 3.30 mm? c) What is the probability that a glass sheet is between 3.25mm and 3.75mm? d) What is the value of c for which there is a 99% probability that a glass sheet has a thickness within the interval [3.50 − c, 3.50 + c]?
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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