Parametric tests are statistical methods that assume the data follows a specific distribution, typically a normal distribution. These tests require certain conditions, such as homogeneity of variance and interval or ratio scale data. Common examples include the t-test and ANOVA, which help determine if there are significant differences between groups. These tests are powerful and efficient when their assumptions are met, allowing researchers to make inferences about populations based on sample data. However, if the assumptions are violated, the results may be misleading, making it essential to check the data's suitability for parametric analysis before proceeding.