Given below are two statements:

Statement I: Non-parametric tests are not easy to use and are rather slow i.e. they require labourious computations.

Statement II: Non-parametric tests do not suppose any particular distribution and the consequential assumptions.

In light of the above statements, choose the correct answer from the options given below:

The correct answer is Statement I is false but Statement II is true.
Key PointsStatement I: Non-parametric tests are not easy to use and are rather slow i.e. they require labourious computations.

• The statement "Non-parametric tests are not easy to use and are rather slow, i.e., they require laborious computations" is false.
•  Non-parametric tests do not require any assumptions about the underlying distribution of the data, which makes them useful in situations where the data do not meet the assumptions of parametric tests.
• However, they can be more complex to understand and execute compared to parametric tests, and they may require more time and effort to perform due to the need for extensive computations.
• The level of complexity and computational requirements can vary depending on the specific non-parametric test used and the size and complexity of the data set being analyzed.

Hence, Statement I is False.

Statement II: Non-parametric tests do not suppose any particular distribution and the consequential assumptions.

• The statement "Non-parametric tests do not suppose any particular distribution and the consequential assumptions" is true.
• Non-parametric tests are statistical tests that do not require any assumptions about the underlying distribution of the data.
• Unlike parametric tests, which assume that the data follow a particular distribution (such as normal distribution), non-parametric tests do not require any such assumptions.
• As a result, non-parametric tests can be useful when the data does not meet the assumptions of parametric tests or when the distribution of the data is unknown or ambiguous.
• Non-parametric tests are more flexible in their application and can be used with different types of data, including ordinal and nominal data.

Hence, Statement II is True.