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why should we use non-parametric tests? choose the one false answer. group of answer choices because they are more powerful than parametric tests because when you have quantitative data but assumptions of normality are not met because when you are only using ordered data because when there is no linearity

Respuesta :

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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