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Learn how to identify anomalies in your data using SQL. Understand how to apply mathematical concepts such as mean, standard deviation, and z-score to detect when an anomaly occurred in your data and how to investigate past data to improve and refine the model.

Simple Anomaly Detection using SQL

What is the mean of the following series?

1, 2, 3, 4, 10

What is the mean of the following series?
1, 2, 3, 4, 10

What is the standard deviation of the following series?

1, 2, 3, 4, 10

What is the standard deviation of the following series?
1, 2, 3, 4, 10

What would be the z-score of the value 6.5 in series with an average of 3 and standard deviation of 3.5?

What would be the z-score of the value 6.5 in series with an average of 3 and standard deviation of 3.5?

What would be the z-score of the value 10 in series with an average of 3 and standard deviation of 3.5?


What would be the z-score of the value 10 in series with an average of 3 and standard deviation of 3.5?

If we consider any values with a z-score greater than 1 an anomaly, which of these values will be considered an anomaly?

1, 2, 3, 4, 10

If we consider any values with a z-score greater than 1 an anomaly, which of these values will be considered an anomaly?
1, 2, 3, 4, 10

If we consider any values with a z-score greater than 3 an anomaly, which of these values will be considered an anomaly?

1, 2, 3, 4, 10

If we consider any values with a z-score greater than 3 an anomaly, which of these values will be considered an anomaly?
1, 2, 3, 4, 10

Detecting Anomalies

Analyzing A Server Log

Backtesting

Improving Accuracy

Quiz 1