To provide: A detailed note to explain the reason of Martin being incorrect.

Question

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Answer 1

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 8, Problem 1CRE

To determine

To provide: A detailed note to explain the reason of Martin being incorrect.

Expert Solution & Answer

Explanation of Solution

Given:

Three conditions are most to least important.

Concept used:

Following are the main conditions to perform independence:

Data must be random.
Values must be independent of each other.
Data must be normally distributed.

All of the above-mentioned conditions are important due to the following reasons:

(a). Randomness is important for the representation of entire true population. Without randomization condition it is not possible to perform inferences.

(b). Normality is the second condition that is must to perform inference because large sample size (that is above 30) is the representation of the population.

(c) The condition that is not important is the condition of independence because the independence could be assumed even if the size of the sample is below the 10% of the size of population.

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Answer 2

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 8, Problem 1CRE

To determine

To provide: A detailed note to explain the reason of Martin being incorrect.

Expert Solution & Answer

Explanation of Solution

Given:

Three conditions are most to least important.

Concept used:

Following are the main conditions to perform independence:

Data must be random.
Values must be independent of each other.
Data must be normally distributed.

All of the above-mentioned conditions are important due to the following reasons:

(a). Randomness is important for the representation of entire true population. Without randomization condition it is not possible to perform inferences.

(b). Normality is the second condition that is must to perform inference because large sample size (that is above 30) is the representation of the population.

(c) The condition that is not important is the condition of independence because the independence could be assumed even if the size of the sample is below the 10% of the size of population.

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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 8, Problem 1CRE

To determine

To provide: A detailed note to explain the reason of Martin being incorrect.

Expert Solution & Answer

Explanation of Solution

Given:

Three conditions are most to least important.

Concept used:

Following are the main conditions to perform independence:

Data must be random.
Values must be independent of each other.
Data must be normally distributed.

All of the above-mentioned conditions are important due to the following reasons:

(a). Randomness is important for the representation of entire true population. Without randomization condition it is not possible to perform inferences.

(b). Normality is the second condition that is must to perform inference because large sample size (that is above 30) is the representation of the population.

(c) The condition that is not important is the condition of independence because the independence could be assumed even if the size of the sample is below the 10% of the size of population.

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Subscribe now to access step-by-step solutions to millions of textbook problems written by subject matter experts!

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 8, Problem 1CRE

To determine

To provide: A detailed note to explain the reason of Martin being incorrect.

Expert Solution & Answer

Explanation of Solution

Given:

Three conditions are most to least important.

Concept used:

Following are the main conditions to perform independence:

Data must be random.
Values must be independent of each other.
Data must be normally distributed.

All of the above-mentioned conditions are important due to the following reasons:

(a). Randomness is important for the representation of entire true population. Without randomization condition it is not possible to perform inferences.

(b). Normality is the second condition that is must to perform inference because large sample size (that is above 30) is the representation of the population.

(c) The condition that is not important is the condition of independence because the independence could be assumed even if the size of the sample is below the 10% of the size of population.

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Answer 5

Chapter 8, Problem 1CRE

To determine

To provide: A detailed note to explain the reason of Martin being incorrect.

Expert Solution & Answer

Explanation of Solution

Given:

Three conditions are most to least important.

Concept used:

Following are the main conditions to perform independence:

Data must be random.
Values must be independent of each other.
Data must be normally distributed.

All of the above-mentioned conditions are important due to the following reasons:

(a). Randomness is important for the representation of entire true population. Without randomization condition it is not possible to perform inferences.

(b). Normality is the second condition that is must to perform inference because large sample size (that is above 30) is the representation of the population.

(c) The condition that is not important is the condition of independence because the independence could be assumed even if the size of the sample is below the 10% of the size of population.

Answer 6

Chapter 8, Problem 1CRE

To determine

To provide: A detailed note to explain the reason of Martin being incorrect.

Expert Solution & Answer

Explanation of Solution

Given:

Three conditions are most to least important.

Concept used:

Following are the main conditions to perform independence:

Data must be random.
Values must be independent of each other.
Data must be normally distributed.

All of the above-mentioned conditions are important due to the following reasons:

(a). Randomness is important for the representation of entire true population. Without randomization condition it is not possible to perform inferences.

(b). Normality is the second condition that is must to perform inference because large sample size (that is above 30) is the representation of the population.

(c) The condition that is not important is the condition of independence because the independence could be assumed even if the size of the sample is below the 10% of the size of population.

Answer 7

Chapter 8, Problem 1CRE

To determine

To provide: A detailed note to explain the reason of Martin being incorrect.

Answer 8

Expert Solution & Answer

Explanation of Solution

Given:

Three conditions are most to least important.

Concept used:

Following are the main conditions to perform independence:

Data must be random.
Values must be independent of each other.
Data must be normally distributed.

All of the above-mentioned conditions are important due to the following reasons:

(a). Randomness is important for the representation of entire true population. Without randomization condition it is not possible to perform inferences.

(b). Normality is the second condition that is must to perform inference because large sample size (that is above 30) is the representation of the population.

(c) The condition that is not important is the condition of independence because the independence could be assumed even if the size of the sample is below the 10% of the size of population.