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Sagot :
Option B. Because when you have quantitative data, but assumptions of normality are not met. This is because, unlike parametric tests, non-parametric tests do not make assumptions about the data's underlying distribution.
Why should we use non-parametric tests?
- Option B. Because when you have quantitative data, but assumptions of normality are not met.
Non-parametric tests are often used when dealing with data that is not normally distributed, as they allow for a more accurate analysis of such data. They can also be used when a linearity of the data cannot be assumed and when dealing with ordinal data. Non-parametric tests are more powerful than parametric tests, which makes them a good choice when a more precise analysis is needed.
Learn more about the Non-parametric tests: https://brainly.com/question/14294503
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