Non-Parametric Tests: Master the Basics with Interactive Quizzes

Question 1

Which of the following is **NOT** a characteristic of the Kruskal-Wallis test?

Accepted Answer

It is generally less powerful than the Mann-Whitney U test for small sample sizes.

Answer

It is a non-parametric test, making it suitable for data that does not follow a normal distribution.

Answer

It can be used to compare three or more independent samples.

Question 2

What is the main reason for conducting a post-hoc test in non-parametric analysis?

Accepted Answer

To make pairwise comparisons and find significant differences between specific groups after an overall significant result in the initial non-parametric test.

Answer

To determine the overall significance of the non-parametric test.

Answer

To check the normality of the data before conducting the non-parametric test.

Answer

To calculate the effect size of the non-parametric test.

Question 3

Which of the following is a defining characteristic of non-parametric tests?

Accepted Answer

They do not assume a specific distribution of the data.

Answer

They can only test for differences in means.

Answer

They are more powerful than parametric tests in all situations.

Answer

They are suitable for large sample sizes only.

Question 4

Which of the following is NOT a type of non-parametric test commonly used in research?

Accepted Answer

t-test

Answer

Kruskal-Wallis test

Answer

chi-square test

Answer

Mann-Whitney U test

Question 5

Which non-parametric test is appropriate for comparing two independent groups?

Accepted Answer

Mann-Whitney U test

Answer

t-test

Answer

chi-square test

Answer

Kruskal-Wallis test

Question 6

What are the main assumptions of the chi-square test?

Accepted Answer

The data are in categorical form and the expected frequencies are sufficiently large.

Answer

The data are normally distributed with equal variances.

Answer

The variables are measured on a continuous scale.

Answer

The sample size is particularly large.

Question 7

Which of the following is NOT an advantage of using non-parametric tests?

Accepted Answer

They are consistently more powerful than parametric tests.

Answer

They do not require the assumption of normality.

Answer

They can be used with smaller sample sizes.

Answer

They are typically easier to interpret.

Question 8

When would you use a Kruskal-Wallis test?

Accepted Answer

To compare three or more independent groups.

Answer

To test for differences in means.

Answer

To test for the independence of two categorical variables.

Answer

To compare two independent groups.

Question 9

What is the null hypothesis for a chi-square test of independence?

Accepted Answer

The two categorical variables are independent.

Answer

The population proportion is equal to a specific value.

Answer

The data are normally distributed.

Answer

The two means are equal.

Question 10

Which of the following is a strength of non-parametric tests?

Accepted Answer

Their validity is not affected by outliers in the data.

Answer

They require less computational effort.

Answer

They can be used to test any type of hypothesis.

Answer

They are more accurate than parametric tests.

Question 11

What is the key difference between a parametric test and a non-parametric test?

Accepted Answer

Parametric tests assume a specific distribution of the data, while non-parametric tests do not.

Answer

Parametric tests are always more powerful than non-parametric tests.

Answer

Parametric tests require larger sample sizes than non-parametric tests.

Answer

Non-parametric tests are easier to interpret than parametric tests.

Question 12

Which of the following is a limitation of non-parametric tests?

Accepted Answer

They can be less efficient (i.e. less powerful) than parametric tests when the data are normally distributed.

Answer

They are difficult to interpret.

Answer

They cannot be used to test complex hypotheses.

Answer

They require very large sample sizes.

Question 13

Which assumption is NOT required for conducting a non-parametric test?

Accepted Answer

Data follows a normal distribution

Answer

Data is independent

Answer

Data is randomly sampled

Answer

Data is continuous

Question 14

Which non-parametric test is used to compare the medians of two independent groups?

Accepted Answer

Mann-Whitney U test

Answer

Chi-square test

Answer

Kruskal-Wallis test

Answer

Kolmogorov-Smirnov test

Question 15

In a Kruskal-Wallis test, what is the null hypothesis?

Accepted Answer

The medians of all groups are equal

Answer

The proportion of successes in the first group is greater than the proportion of successes in the second group

Answer

The variance of the first group is greater than the variance of the second group

Answer

The mean of the first group is greater than the mean of the second group

Question 16

Which of the following is a disadvantage of using non-parametric tests?

Accepted Answer

They can be less powerful than parametric tests

Answer

They cannot be used with large sample sizes

Answer

They are more difficult to perform than parametric tests

Answer

They are not as versatile as parametric tests

Question 17

In a chi-square test, what does a p-value of 0.03 indicate?

Accepted Answer

The null hypothesis is rejected at the 0.05 significance level

Answer

The test is not statistically significant

Answer

The alternative hypothesis is accepted

Answer

The data is normally distributed

Question 18

When using a non-parametric test, it is essential to:

Accepted Answer

Check the assumptions of the test

Answer

Transform the data to normality

Answer

Ignore the presence of outliers

Answer

Use a large sample size

Question 19

Which of the following non-parametric tests is used to compare proportions between two independent groups?

Accepted Answer

Chi-square test

Answer

t-test

Answer

Kruskal-Wallis test

Answer

Mann-Whitney U test

Question 20

A researcher wants to compare the median incomes of three different cities from a non-parametric perspective. Which test would be most appropriate?

Accepted Answer

Kruskal-Wallis test

Answer

Chi-square test

Answer

Mann-Whitney U test

Answer

ANOVA

Question 21

Which of the following assumptions is NOT required for the Mann-Whitney U test?

Accepted Answer

The data is normally distributed.

Answer

The data is continuous.

Answer

The two groups are independent.

Answer

The variances of the two groups are equal.

Question 22

A researcher wants to determine if there is a significant difference in the median scores between two groups on a standardized test. The raw data for both groups is available. Which statistical test is most appropriate for this purpose?

Accepted Answer

Mann-Whitney U test

Answer

t-test

Answer

F-test

Answer

Chi-square test

Question 23

Which is a primary advantage of using non-parametric tests?

Accepted Answer

Non-parametric tests do not assume a normal distribution of the data.

Answer

Non-parametric tests are more powerful than parametric tests.

Answer

Non-parametric tests are easier to interpret than parametric tests.

Answer

Non-parametric tests do not require raw data.

Question 24

What is the null hypothesis for a non-parametric test?

Accepted Answer

There is no significant difference between the groups.

Answer

The data is normally distributed.

Answer

The variances of the groups are equal.

Answer

There is a significant difference between the groups.

Question 25

What is the purpose of a critical value in a non-parametric test?

Accepted Answer

To determine the region of rejection and non-rejection of the null hypothesis.

Answer

To determine the mean of the data.

Answer

To determine the median of the data.

Question 26

Which is a potential drawback of using non-parametric tests?

Accepted Answer

Non-parametric tests can be less powerful than parametric tests when the data is normally distributed.

Answer

Non-parametric tests cannot be used with large sample sizes.

Answer

Non-parametric tests are more difficult to interpret than parametric tests.

Answer

Non-parametric tests require the assumption of a normal distribution.

Question 27

Which of the following is a potential limitation of non-parametric tests?

Accepted Answer

They can be less powerful than parametric tests when the assumptions of parametric tests are met

Answer

They are more difficult to interpret than parametric tests

Answer

They require a larger sample size than parametric tests

Question 28

In a chi-square test, the expected frequency for a cell is calculated as:

Accepted Answer

(Row Total x Column Total) / Grand Total

Answer

Grand Total / (Row Total + Column Total)

Answer

(Row Total + Column Total) / Grand Total

Answer

(Row Total - Column Total) / Grand Total

Question 29

Which of the following is NOT a step in conducting a non-parametric test?

Accepted Answer

Transform the data to meet the assumptions of a parametric test

Answer

State the null and alternative hypotheses

Answer

Calculate the test statistic

Question 30

What is the purpose of a contingency table in a chi-square test?

Accepted Answer

To display the observed and expected frequencies for each category combination

Answer

To determine the degrees of freedom

Answer

To calculate the test statistic

Question 31

When conducting a non-parametric test, it is important to:

Accepted Answer

Consider the assumptions and limitations of the test

Answer

Transform the data to meet the assumptions of a parametric test

Answer

Use the largest possible sample size