Non-Parametric Tests Quiz

What are non-parametric tests?

• Tests that require normal distribution of the data

• Tests that are only used for qualitative data

• Statistical tests that only work for large sample sizes

• Statistical tests that do not make any assumptions about the distribution of the data

When are non-parametric tests used?

• When the sample size is large

• When the data meets the assumptions of parametric tests

• When the data is normally distributed

• When the data does not meet the assumptions of parametric tests

What is the difference between parametric and non-parametric tests?

• Parametric tests do not make any assumptions about the population parameters, while non-parametric tests make assumptions about the population parameters.

• Parametric tests make assumptions about the sample parameters, while non-parametric tests make assumptions about the population parameters.

• Parametric tests make assumptions about the population parameters, while non-parametric tests make assumptions about the sample parameters.

• Parametric tests make assumptions about the population parameters, while non-parametric tests do not make any assumptions about the population parameters.

What are the advantages of using non-parametric tests?

• Less flexibility and applicability to a wider range of data

• Limited use in real-world scenarios

• More accuracy and precision in results

• More flexibility and applicability to a wider range of data

What are the limitations of non-parametric tests?

• Limitations may include sensitivity to outliers, less power compared to parametric tests, and assumptions about the shape of the distribution.

• Non-parametric tests assume a normal distribution

• Non-parametric tests are more powerful than parametric tests

• Non-parametric tests have no limitations

Explain the concept of the Mann-Whitney U test.

• The Mann-Whitney U test compares three or more independent groups

• The Mann-Whitney U test compares two independent groups when the data is not normally distributed.

• The Mann-Whitney U test is only applicable to normally distributed data

• The Mann-Whitney U test is used for paired data

What is the Wilcoxon signed-rank test used for?

• To compare two related groups when the data is not normally distributed.

• To compare two independent groups when the data is normally distributed.

• To calculate the mean of a single group of data.

• To determine the correlation between two variables.

What is the Kruskal-Wallis test?

• A statistical test for comparing three or more independent groups that are not normally distributed.

• A test for comparing the mean of a single group

• A test for comparing paired samples

• A test for comparing two independent groups

When should you use the Friedman test?

• When comparing two unrelated groups on a parametric measure.

• When comparing a single group at different time points.

• When comparing multiple related groups on a non-parametric measure.

• When comparing multiple unrelated groups on a non-parametric measure.