Finding outliers with z-scores

The normal distribution is ubiquitous in the natural world and is the most common distribution. This is why the z-score method can be one of the quickest methods for detecting outliers.

Recall the rule of thumb from the video: if a sample is more than three standard away deviations from the mean, you can consider it an extreme value.

However, recall also that the z-score method should be approached with caution. This method is appropriate only when we are confident our data comes from a normal distribution. Otherwise, the results might be misleading.

The prices distribution has been loaded for you.

Import the zscore function from the relevant scipy module.
Find the z-scores of prices and store them into scores.
Create a boolean mask named is_over_3 to check if the absolute values of scores are greater than 3.
Use the mask to filter prices for outliers.

Exercise

Finding outliers with z-scores

Instructions