Parametric statistics refers to a set of statistical techniques that assume the data follows a specific distribution, typically a normal distribution. These methods rely on parameters, such as the mean and standard deviation, to summarize and analyze data. Common parametric tests include the t-test and ANOVA, which help determine if there are significant differences between groups. These techniques are powerful when the assumptions are met, as they can provide more accurate results than non-parametric methods. However, if the data does not meet these assumptions, the results may be misleading, making it essential to check the data's distribution before applying parametric tests.