In statistics, the term "parametric" indicates data that is:

The term "parametric" specifically refers to statistical methods and techniques that assume the data follows a certain distribution, most commonly the normal distribution. When data is described as parametric, it typically implies that the underlying population from which the samples are drawn conforms to this normal distribution, allowing for the use of various parametric statistical tests like t-tests and ANOVA.

Parametric tests take advantage of the properties of normally distributed data, allowing for more powerful statistical inferences as compared to non-parametric tests, which do not rely on such distributional assumptions. Understanding that parametric methods depend on this normality assumption helps clarify why the conclusion drawn about parametric data being normally distributed is accurate and foundational to the practice of statistical analysis.