Thestandard deviation uses of emperical rule.

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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.

Chapter 4, Problem 28CAP

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To calculate:

Thestandard deviation uses of emperical rule.

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Suppose that a sports reporter claims the average football game lasts 3 hours, and you believe it's more than that. Your random sample of 35 games has an average time of 3.25 hours. Assume that the population standard deviation is 1 hour. Use a = 0.05. What do you conclude?

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Table 5: Measurement Data for Question 9 Part Number Op-1, M-1 Op-1, M-2 | Op-2, M-1 Op-2, M-2 | Op-3, M-1 Op-3, M-2 1 21 20 20 20 19 21 2 24 23 24 24 23 24 3 4 5 6 7 8 9 10 11 21 12 8222332 201 21 20 22 20 22 27 27 28 26 27 28 19 18 19 21 24 21 22 19 17 18 24 23 25 25 23 26 20 20 18 19 17 13 23 25 25 2 3 3 3 3 2 3 18 18 21 21 23 22 24 22 20 19 23 24 25 24 20 21 19 18 25 25 14 24 24 23 25 24 15 29 30 30 28 31 16 26 26 25 26 25 17 20 20 19 20 20 843882388 20 18 25 20 19 25 25 30 27 20 18 19 21 19 19 21 23 19 25 26 25 24 25 25 20 19 19 18 17 19 17 Question 9 A measurement systems experiment involving 20 parts, three operators (Op-1, Op-2, Op-3), and two measure- ments (M-1, M-2) per part is shown in Table 5. (a) Estimate the repeatability and reproducibility of the gauge. (b) What is the estimate of total gauge variability?" (c) If the product specifications are at LSL = 6 and USL 60, what can you say about gauge capability?

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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.

Chapter 4, Problem 28CAP

To determine

To calculate:

Thestandard deviation uses of emperical rule.

Expert Solution & Answer

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Check out a sample textbook solution

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Answer 3

Question

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.

Chapter 4, Problem 28CAP

To determine

To calculate:

Thestandard deviation uses of emperical rule.

Expert Solution & Answer

Want to see the full answer?

Check out a sample textbook solution

See solution

Answer 4

Question

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.

Chapter 4, Problem 28CAP

To determine