Explain whether the regression error assumptions, normality and the constant variance are violated or not.

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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 12.8, Problem 34SE

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Explain whether the regression error assumptions, normality and the constant variance are violated or not.

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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?

Question 5 A fraction nonconforming control chart with center line 0.10, UCL = 0.19, and LCL = 0.01 is used to control a process. (a) If three-sigma limits are used, find the sample size for the control charte 2 (b) Use the Poisson approximation to the binomial to find the probability of type I error. (c) Use the Poisson approximation to the binomial to find the probability of type II error if the process fraction defective is actually p = 0.20.

Question 8 Ten parts are measured three times by the same operator in a gauge capability study. The data are shown in Table 4. (a) Describe the measurement error that results from the use of this gauge. I (b) Estimate total variability and product variability. (c) What percentage of total variability is due to the gauge? (d) If specifications on the part are at 100±15, find the P/T ratio for this gauge. Comment on the adequacy of the gauge. 3 Table 4: Measurement Data for Question 8 Part Number Measurement 1 Measurement 2 Measurement 3 1 2 100 95 101 100 93 97 3 101 103 100 4 96 95 97 5 98 98 96 6 99 98 98 7889 95 97 98 100 99 98 100 100 97 10 100 98 98 99

Answer 2

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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 12.8, Problem 34SE

To determine

Explain whether the regression error assumptions, normality and the constant variance are violated or not.

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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 12.8, Problem 34SE

To determine

Explain whether the regression error assumptions, normality and the constant variance are violated or not.

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Answer 4

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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 12.8, Problem 34SE

To determine

Explain whether the regression error assumptions, normality and the constant variance are violated or not.

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Answer 5

Chapter 12.8, Problem 34SE

To determine

Explain whether the regression error assumptions, normality and the constant variance are violated or not.

Answer 6

Chapter 12.8, Problem 34SE

To determine

Explain whether the regression error assumptions, normality and the constant variance are violated or not.

Answer 7

Chapter 12.8, Problem 34SE

To determine

Explain whether the regression error assumptions, normality and the constant variance are violated or not.

Answer 8

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Answer 9

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Answer 11

Ch. 12.1 - For each sample, do a test for zero correlation....Ch. 12.1 - Instructions for Exercises 12.2 and 12.3: (a) Make...Ch. 12.1 - Prob. 3SE Ch. 12.1 - Prob. 4SE Ch. 12.1 - Instructions for exercises 12.412.6: (a) Make a...Ch. 12.1 - Prob. 6SE Ch. 12.2 - (a) Interpret the slope of the fitted regression...Ch. 12.2 - (a) Interpret the slope of the fitted regression...Ch. 12.2 - Prob. 9SE Ch. 12.2 - (a) Interpret the slope of the fitted regression...

Explain whether the regression error assumptions, normality and the constant variance are violated or not.

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Explain whether the regression error assumptions, normality and the constant variance are violated or not.

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