What is the difference between parametric and nonparametric hypothesis testing?
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- Опубликовано: 3 июл 2024
- Hi, in this video I explain the difference between parametric and non-parametric tests! You want to calculate a hypothesis test, but don't know exactly what the difference is between a parametric and non-parametric test and are wondering when to use which test. If you want to calculate a hypothesis test, you must first check the assumptions for the respective hypothesis test. One of the most common assumption is that the data used must be normally distributed. Put simply, if your data is normally distributed, parametric tests are used, e.g. the t-test, analysis of variance or pearson correlation. If your data is not normally distributed, non-parametric tests are used, e.g. the Mann-Whitney U test or the Spearman correlation.
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0:00 What are parametric and non-parametric hypothesis tests?
1:54 Pearson correlation vs. the Spearman correlation
4:00 t-test for independent samples vs. Mann Whitney U test
5:43 List of parametric and non-parametric hypothesis tests.
6:17 Calculating parametric and non-parametric hypothesis tests with DATAtab
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Extremely helpful explanation! Thank you so much for sharing 😊
Glad it was helpful!
These videos are great. Thank you!
Glad you like them! Regards, Hannah
Very clear. Thank you very much.
Glad it was helpful!
Great video! Please add a "Thanks" button to videos like this.
Hi Greg, many thanks : ) I have just added it : ) I hope it is working : ) Regards Hannah
Thanks sensei.
Any time! : )
Thank you ma'am.
Glad it was helpful and many thanks for your feedback! Regards Hannah
FANTASTIC 🎉🎉🎉
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Many thanks! : )