A common rule to identify outliers is the 1.5*IQR rule, meaning any data points that are more than 1.5*IQR above the Q3 (the third quartile) or below Q1 (the first quartile).
In this post, I am going to show you how to implement this rule in Tableau to identify outliers, an important step in data exploration.
Compute Q1, Q3, and IQR
window_percentile function to compute the third quartile and first quartile for the entire table. Use Q3-Q1 to get IQR.
Compute Q1-1.5IQR as the lower bound
Compute Q3+1.5IQR as the upper bound
The Outlier Flag
Specify what constitutes an outlier for the target metric.
Indicate Outliers and Bounds in Chart
- Use reference band to the lower bound to Q1-1.5IQR and upper bound to be Q3+1.5IQR
- Use the outlier flag for color and shape
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