Parametric.
If the distribution is parametric then yes.
yes
Parametric statistical tests assume that your data are normally distributed (follow a classic bell-shaped curve). An example of a parametric statistical test is the Student's t-test.Non-parametric tests make no such assumption. An example of a non-parametric statistical test is the Sign Test.
* Always when the assumptions for the specific test (as there are many parametric tests) are fulfilled. * When you want to say something about a statistical parameter.
Parametric.
If the distribution is parametric then yes.
yes
Parametric statistical tests assume that your data are normally distributed (follow a classic bell-shaped curve). An example of a parametric statistical test is the Student's t-test.Non-parametric tests make no such assumption. An example of a non-parametric statistical test is the Sign Test.
Parametric for one set?! Yeah
* Always when the assumptions for the specific test (as there are many parametric tests) are fulfilled. * When you want to say something about a statistical parameter.
Binomial is a non- parametric test. Since this binomial test of significance does not involve any parameter and therefore is non parametric in nature, the assumption that is made about the distribution in the parametric test is therefore not assumed in the binomial test of significance. In the binomial test of significance, it is assumed that the sample that has been drawn from some population is done by the process of random sampling. The sample on which the binomial test of significance is conducted by the researcher is therefore a random sample.
A classic would be the Kolmogorov-Smirnov test.
It is not.It is not.It is not.It is not.
The Fisher F-test for Analysis of Variance (ANOVA).
t-test
kendall tau