input: Write a python function to identify anomalies in a dataset based on z-scores, where a z-score greater than 3 or less than -3 is considered an anomaly.
  assert identify_anomalies([1, 2, 3, 4, 100, 6, 7, 8, -100]) == [100, -100]
  assert identify_anomalies([10, 12, 15, 14, 13, 40, 10, 12, 11]) == [40]
  assert identify_anomalies([1, 2, 2, 2, 2, 2, 2, 2, 2, 100]) == [100]
output: import numpy as np
  
  def identify_anomalies(data):
      mean = np.mean(data)
      std_dev = np.std(data)
      anomalies = [x for x in data if (x - mean) / std_dev > 3 or (x - mean) / std_dev < -3]
      return anomalies