Uploaded March 2024 | Updated September 2026, 4 days ago
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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► Tutorial
numiqo.com/tutorial/parametric-and-non-parametric-tests
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
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.
► Statistics calculator
numiqo.com/statistics-calculator/hypothesis-test
► EBOOK
numiqo.com/statistics-book
► Tutorial
numiqo.com/tutorial/parametric-and-non-parametric-tests
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
![Levenes test [Test for variance equality]](https://i.ytimg.com/vi/x51GDTiPIfI/mqdefault.jpg "Levenes test [Test for variance equality]
Levenes test tests the hypothesis that the variances are equal in different groups. Many statistical testing procedures require that there is equal variance in the samples. How can it now be checked whether the variances are homogeneous, i.e. whether there is equality of variance? This is where the Levene test helps. The Levene test checks whether several groups have the same variance in the population.
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https://numiqo.com/tutorial/levene-test
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https://numiqo.com/statistics-book")
![Wilcoxon Test [in 49 sec.] #shorts](https://i.ytimg.com/vi/xNlYw3tSl-k/mqdefault.jpg "Wilcoxon Test [in 49 sec.] #shorts
What is the Wilcoxon Test in statistics? A simplified explanation in under a minute. Non parametric Test for two dependent samples. (Data analytics)
#statistics #math #research #datascience #dataanalysis #thesis #stats #researcher #thesiswriting #science")
![Boxplot [in 60 sec.] #shorts](https://i.ytimg.com/vi/xkzsxmZfpZw/mqdefault.jpg "Boxplot [in 60 sec.] #shorts
Boxplots are used in statistics to graphically display different parameters at a glance. This is why boxplots are so difficult to understand at the beginning, because a lot of information about the data is provided in one diagram. Among other things, the median, the interquartile range and the outliers can be read in a boxplot.")
![Regression analysis [in 57 sec.] #shorts](https://i.ytimg.com/vi/z70upVhz9d8/mqdefault.jpg "Regression analysis [in 57 sec.] #shorts
Regression is a statistical method that allows modeling relationships between a dependent variable and one or more independent variables. A regression analysis makes it possible to infer or predict another variable on the basis of one or more variables.
#statistics")
