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Parametric Assumptions

Parametric assumptions are tests that need to be run to decide whether the data can be tested using a parametric or a non-parametric test. The parametric tests are the stronger of the two. However, the data must fulfil all of the assumptions if it is to be used. In correlations, Pearson’s R is the parametric test and Spearman’s Rho is the non-parametric test. 

The four parametric assumptions tests for correlations are:

  1. Data must be interval (scale/ordinal)
  2. Data must be normally distributed
  3. Data must have homoscedasticity 
  4. Data must be linear

We will learn more about these in this topic.