when data is not normally distributed which nonparametric test to be used if you have 2 groups experimental and control group with 3 levels pre post and follow-up
also, can we use parametric test even if data is not normally distributed what are conditions. and what is bootstrap and how it helps in parametric test when data is not normally distributed. kindly answer these question with the best of your knowledge as early as possible.
thank you.
Kruskal-Wallis H test @Jawaria Afzal.
Yes, parametric test can be used when data is not normally distributed with these conditions
For example:
A 1-sample t-test can be used with non-normal data if the sample size is greater than 20.
A 2-sample t-test requires each group to have more than 15 observations.
For a One-Way ANOVA, if you have 2-9 groups, each group should have more than 15 observation
Bootstrapping is a statistical procedure that involves resampling a single dataset to create many simulated samples. This method allows you to calculate standard errors, construct confidence intervals, and perform hypothesis testing for various sample statistics without relying on the normality assumption.
In the context of parametric tests, bootstrapping can be particularly useful because it:
Does not require the assumption of normality.
Can be applied to estimate the sampling distribution of a statistic.
Is valid under a broader range of conditions compared to traditional methods.
- Badges
- Science topic
- Similar topics
- Psychology