parametric statistics

Parametric statistics refers to a branch of statistical analysis that makes assumptions about the underlying data's distribution, often assuming it follows a specific pattern like a normal (bell curve) distribution. By doing so, it uses parameters such as the mean and standard deviation to summarize and analyze the data. This approach allows for more precise and efficient analysis when the assumptions are met. Examples include t-tests and ANOVA. However, if the data doesn’t fit the assumed distribution, results can be misleading, so checking assumptions is important before applying parametric methods.