Mention the three ways that non-parametric tests differ from parametric tests.

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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 17, Problem 1FP

To determine

Mention the three ways that non-parametric tests differ from parametric tests.

Expert Solution & Answer

Answer to Problem 1FP

The three ways that non-parametric test differ from parametric tests are,

1. The non-parametric test is not used for making the inferences about the population parameters.
2. For any type of distributed data non-parametric test can be used.
3. The data that is measured on either nominal or ordinal scale is analyzed in non-parametric test.

Explanation of Solution

Parametric test:

The parametric test is used for making the inferences about the population parameters.
The parametric test can be used only when the data is normally distributed.
The parametric test analyzes the data that is measured on either interval or ratio scale.

Non-Parametric test:

The non-parametric test is not used for making the inferences about the population parameters. It can be used for testing the hypothesized relations in the population.
The parametric test can be used with any type distribution, it is not necessary that data should be normally distributed.
The parametric test analyzes the data that is measured on either nominal or ordinal scale.

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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 17, Problem 1FP

To determine

Mention the three ways that non-parametric tests differ from parametric tests.

Expert Solution & Answer

Answer to Problem 1FP

The three ways that non-parametric test differ from parametric tests are,

1. The non-parametric test is not used for making the inferences about the population parameters.
2. For any type of distributed data non-parametric test can be used.
3. The data that is measured on either nominal or ordinal scale is analyzed in non-parametric test.

Explanation of Solution

Parametric test:

The parametric test is used for making the inferences about the population parameters.
The parametric test can be used only when the data is normally distributed.
The parametric test analyzes the data that is measured on either interval or ratio scale.

Non-Parametric test:

The non-parametric test is not used for making the inferences about the population parameters. It can be used for testing the hypothesized relations in the population.
The parametric test can be used with any type distribution, it is not necessary that data should be normally distributed.
The parametric test analyzes the data that is measured on either nominal or ordinal scale.

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

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 17, Problem 1FP

To determine

Mention the three ways that non-parametric tests differ from parametric tests.

Expert Solution & Answer

Answer to Problem 1FP

The three ways that non-parametric test differ from parametric tests are,

1. The non-parametric test is not used for making the inferences about the population parameters.
2. For any type of distributed data non-parametric test can be used.
3. The data that is measured on either nominal or ordinal scale is analyzed in non-parametric test.

Explanation of Solution

Parametric test:

The parametric test is used for making the inferences about the population parameters.
The parametric test can be used only when the data is normally distributed.
The parametric test analyzes the data that is measured on either interval or ratio scale.

Non-Parametric test:

The non-parametric test is not used for making the inferences about the population parameters. It can be used for testing the hypothesized relations in the population.
The parametric test can be used with any type distribution, it is not necessary that data should be normally distributed.
The parametric test analyzes the data that is measured on either nominal or ordinal scale.

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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 17, Problem 1FP

To determine

Mention the three ways that non-parametric tests differ from parametric tests.

Expert Solution & Answer

Answer to Problem 1FP

The three ways that non-parametric test differ from parametric tests are,

1. The non-parametric test is not used for making the inferences about the population parameters.
2. For any type of distributed data non-parametric test can be used.
3. The data that is measured on either nominal or ordinal scale is analyzed in non-parametric test.

Explanation of Solution

Parametric test:

The parametric test is used for making the inferences about the population parameters.
The parametric test can be used only when the data is normally distributed.
The parametric test analyzes the data that is measured on either interval or ratio scale.

Non-Parametric test:

The non-parametric test is not used for making the inferences about the population parameters. It can be used for testing the hypothesized relations in the population.
The parametric test can be used with any type distribution, it is not necessary that data should be normally distributed.
The parametric test analyzes the data that is measured on either nominal or ordinal scale.

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Answer 5

Chapter 17, Problem 1FP

To determine

Mention the three ways that non-parametric tests differ from parametric tests.

Expert Solution & Answer

Answer to Problem 1FP

The three ways that non-parametric test differ from parametric tests are,

1. The non-parametric test is not used for making the inferences about the population parameters.
2. For any type of distributed data non-parametric test can be used.
3. The data that is measured on either nominal or ordinal scale is analyzed in non-parametric test.

Explanation of Solution

Parametric test:

The parametric test is used for making the inferences about the population parameters.
The parametric test can be used only when the data is normally distributed.
The parametric test analyzes the data that is measured on either interval or ratio scale.

Non-Parametric test:

The non-parametric test is not used for making the inferences about the population parameters. It can be used for testing the hypothesized relations in the population.
The parametric test can be used with any type distribution, it is not necessary that data should be normally distributed.
The parametric test analyzes the data that is measured on either nominal or ordinal scale.

Answer 6

Chapter 17, Problem 1FP

To determine

Mention the three ways that non-parametric tests differ from parametric tests.

Expert Solution & Answer

Answer to Problem 1FP

The three ways that non-parametric test differ from parametric tests are,

1. The non-parametric test is not used for making the inferences about the population parameters.
2. For any type of distributed data non-parametric test can be used.
3. The data that is measured on either nominal or ordinal scale is analyzed in non-parametric test.

Explanation of Solution

Parametric test:

The parametric test is used for making the inferences about the population parameters.
The parametric test can be used only when the data is normally distributed.
The parametric test analyzes the data that is measured on either interval or ratio scale.

Non-Parametric test:

The non-parametric test is not used for making the inferences about the population parameters. It can be used for testing the hypothesized relations in the population.
The parametric test can be used with any type distribution, it is not necessary that data should be normally distributed.
The parametric test analyzes the data that is measured on either nominal or ordinal scale.

Answer 7

Chapter 17, Problem 1FP

To determine

Mention the three ways that non-parametric tests differ from parametric tests.

Answer 8

Expert Solution & Answer

Answer to Problem 1FP

The three ways that non-parametric test differ from parametric tests are,

1. The non-parametric test is not used for making the inferences about the population parameters.
2. For any type of distributed data non-parametric test can be used.
3. The data that is measured on either nominal or ordinal scale is analyzed in non-parametric test.

Answer 9

Expert Solution & Answer

Answer 10

Expert Solution & Answer

Answer 11

Explanation of Solution

Parametric test:

The parametric test is used for making the inferences about the population parameters.
The parametric test can be used only when the data is normally distributed.
The parametric test analyzes the data that is measured on either interval or ratio scale.

Non-Parametric test:

The non-parametric test is not used for making the inferences about the population parameters. It can be used for testing the hypothesized relations in the population.
The parametric test can be used with any type distribution, it is not necessary that data should be normally distributed.
The parametric test analyzes the data that is measured on either nominal or ordinal scale.

Answer 12

Ch. 17.2 - Prob. 1.1LC Ch. 17.2 - Prob. 1.2LC Ch. 17.2 - Prob. 1.3LC Ch. 17.2 - Prob. 1.4LC Ch. 17.3 - Prob. 2.1LC Ch. 17.3 - Prob. 2.2LC Ch. 17.5 - Prob. 3.1LC Ch. 17.5 - Prob. 3.2LC Ch. 17.5 - Prob. 3.3LC Ch. 17.6 - Prob. 4.1LC

Mention the three ways that non-parametric tests differ from parametric tests.

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Mention the three ways that non-parametric tests differ from parametric tests.

Answer to Problem 1FP

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