What is the griff rule?

The griff rule, also known as the griffith jones rule, is a guideline used in statistics to determine whether an outlier should be removed from a dataset.

According to the griff rule, an observation can be considered an outlier if it is more than 2.5 standard deviations away from the mean of the dataset. In other words, any data point that falls below the lower bound of Q1 - 2.5IQR or above the upper bound of Q3 + 2.5IQR can be classified as an outlier.

The griff rule is commonly used in conjunction with other statistical methods, such as the IQR method or Z-score method, to identify outliers in a dataset. Outliers can significantly affect the results of statistical analyses, so it is important to carefully consider whether or not to remove them based on established guidelines like the griff rule.