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Can you use parametric and nonparametric tests in the same study?
yes you can use both. Choice of a test depends upon the distribution of your data. Some of the parametric models may be too restrictive to get very good fits to your data. The non-parametric (while being possibly very compute-intense) may be more suitable for your data.
When would you use a parametric test?
If the mean more accurately represents the center of the distribution of your data, and your sample size is large enough, use a parametric test. If the median more accurately represents the center of the distribution of your data, use a nonparametric test even if you have a large sample size.
When do you use a parametric regression test?
Parametric statistical tests are among the most common you’ll encounter. They include t -test, analysis of variance, and linear regression. They are used when the dependent variable is an interval/ratio data variable.
When to use Pearson correlation as a parametric test?
These alternatives are appropriate to use when the dependent variable is measured on an ordinal scale, or if the parametric assumptions are not met. The most frequent parametric test to examine for strength of association between two variables is a Pearson correlation ( r ).
How to select between parametric and non-parametric analyses?
Selecting Between Parametric and Non-Parametric Analyses. A Pearson correlation is used when assessing the relationship between two continuous variables. The non-parametric equivalent to the Pearson correlation is the Spearman correlation ( ρ ), and is appropriate when at least one of the variables is measured on an ordinal scale.
What is the relationship between Pearson correlation and linear regression?
Pearson Correlation and Linear Regression. The Pearson correlation coefficient, r, can take on values between -1 and 1. The further away r is from zero, the stronger the linear relationship between the two variables. The sign of r corresponds to the direction of the relationship. If r is positive, then as one variable increases,…