To explain why data satisfy normality assumption.

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Answer 1

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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 11.5, Problem 11.13E

a)

To determine

To explain why data satisfy normality assumption.

b)

To determine

To explain if data provide sufficient evidence to indicate a difference in mean leaf length.

c)

To determine

To test the difference in mean leaf length of location 1 and location 4.

d)

To determine

To the 99% confidence interval for difference in mean leaf length of location 1 and location 4.

e)

To determine

To explain why ANOVA is needed instead of t-test.

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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 11.5, Problem 11.13E

a)

To determine

To explain why data satisfy normality assumption.

b)

To determine

To explain if data provide sufficient evidence to indicate a difference in mean leaf length.

c)

To determine

To test the difference in mean leaf length of location 1 and location 4.

d)

To determine

To the 99% confidence interval for difference in mean leaf length of location 1 and location 4.

e)

To determine

To explain why ANOVA is needed instead of t-test.

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 11.5, Problem 11.13E

a)

To determine

To explain why data satisfy normality assumption.

b)

To determine

To explain if data provide sufficient evidence to indicate a difference in mean leaf length.

c)

To determine

To test the difference in mean leaf length of location 1 and location 4.

d)

To determine

To the 99% confidence interval for difference in mean leaf length of location 1 and location 4.

e)

To determine

To explain why ANOVA is needed instead of t-test.

Expert Solution & Answer

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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 11.5, Problem 11.13E

a)

To determine

To explain why data satisfy normality assumption.

b)

To determine

To explain if data provide sufficient evidence to indicate a difference in mean leaf length.

c)

To determine

To test the difference in mean leaf length of location 1 and location 4.

d)

To determine

To the 99% confidence interval for difference in mean leaf length of location 1 and location 4.

e)

To determine

To explain why ANOVA is needed instead of t-test.

Expert Solution & Answer

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Answer 5

Chapter 11.5, Problem 11.13E

a)

To determine

To explain why data satisfy normality assumption.

b)

To determine

To explain if data provide sufficient evidence to indicate a difference in mean leaf length.

c)

To determine

To test the difference in mean leaf length of location 1 and location 4.

d)

To determine

To the 99% confidence interval for difference in mean leaf length of location 1 and location 4.

e)

To determine

To explain why ANOVA is needed instead of t-test.

Answer 6

Chapter 11.5, Problem 11.13E

a)

To determine

To explain why data satisfy normality assumption.

Answer 7

Chapter 11.5, Problem 11.13E

a)

To determine

To explain why data satisfy normality assumption.

Answer 8

b)

To determine

To explain if data provide sufficient evidence to indicate a difference in mean leaf length.

Answer 9

b)

To determine

To explain if data provide sufficient evidence to indicate a difference in mean leaf length.

Answer 10

c)

To determine

To test the difference in mean leaf length of location 1 and location 4.

Answer 11

c)

To determine

To test the difference in mean leaf length of location 1 and location 4.

Answer 12

d)

To determine

To the 99% confidence interval for difference in mean leaf length of location 1 and location 4.

Answer 13

d)

To determine

To the 99% confidence interval for difference in mean leaf length of location 1 and location 4.

Answer 14

e)

To determine

To explain why ANOVA is needed instead of t-test.

Answer 15

e)

To determine

To explain why ANOVA is needed instead of t-test.

Answer 16

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Answer 17

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Answer 18

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Answer 19

Ch. 11.5 - Prob. 11.1E Ch. 11.5 - Prob. 11.2E Ch. 11.5 - Prob. 11.3E Ch. 11.5 - Prob. 11.4E Ch. 11.5 - Prob. 11.5E Ch. 11.5 - Prob. 11.6E Ch. 11.5 - These data are observations collected using a...Ch. 11.5 - Prob. 11.8E Ch. 11.5 - Prob. 11.9E Ch. 11.5 - Reducing Hostility A clinical psychologist wished...

To explain why data satisfy normality assumption.

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To explain why data satisfy normality assumption.

To explain if data provide sufficient evidence to indicate a difference in mean leaf length.

To test the difference in mean leaf length of location 1 and location 4.

To the 99% confidence interval for difference in mean leaf length of location 1 and location 4.

To explain why ANOVA is needed instead of t-test.

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