As digital marketers & analysts, we’re often asked to quantify when a metric goes beyond just random variation and becomes an actual “unexpected” result. In cases such as A/B..N testing, it’s easy to calculate a t-test to quantify the difference between two testing populations, but for time-series metrics, using a t-test is likely not appropriate. Anomaly Detection Using...