Parametric inferential tests are carried out on data that follow certain parameters.
The data will be normal (i.e. the distribution parallels the bell curve); numbers can be added, subtracted, multiplied and divided; variances are equal when comparing two or more groups; and the sample should be large and randomly selected. Inferential statistics suggest statements about a population based on a sample from that population.
There are generally more statistical technique options for the analysis of parametric than non-parametric data, and parametric statistics are considered to be the more powerful. Common examples of parametric tests are: correlated t-tests and the Pearson r correlation coefficient.
Woolf, L. M. (n.d.). Introduction to measurement and statistics. Retrieved from http://faculty.webster.edu/woolflm/statwhatis.html
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