Describe any two non parametric test in details
Answer (1)
27th Jan, 2019
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Non parametric tests when your data isn't normal.
Therefore the key is to figure out wether you have a normally distributed data.
For example - if you don't have a graph then how do you figure out if your data is normal distributed?
Check the skewness and kurtosis of the distribution.
A normal distribution has no skew.
If the distribution is not normal then the skewness and kurtosis deviate a lot. You should use a non parametric test like a chi square test.
Another example - another example for the one way anova is that the data comes from a normal distribution. If your data isn't normally distributed then you cannot run the anova, but you can run the non parametric alternative test - kruskal Wallis test.
Wish you all the best!
Non parametric tests when your data isn't normal.
Therefore the key is to figure out wether you have a normally distributed data.
For example - if you don't have a graph then how do you figure out if your data is normal distributed?
Check the skewness and kurtosis of the distribution.
A normal distribution has no skew.
If the distribution is not normal then the skewness and kurtosis deviate a lot. You should use a non parametric test like a chi square test.
Another example - another example for the one way anova is that the data comes from a normal distribution. If your data isn't normally distributed then you cannot run the anova, but you can run the non parametric alternative test - kruskal Wallis test.
Wish you all the best!
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