What are the anomalies in the time series data？
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What are the anomalies in the time series data？
Anomalies in time series data are data points that deviate significantly from the expected pattern or trend of the data. These anomalies can be caused by a variety of factors, such as errors in data collection, changes in the underlying process being measured, or external events that affect the data. Some common types of anomalies in time series data include:
1. Spikes or sudden jumps in the data
2. Dips or sudden drops in the data
3. Seasonal fluctuations that are larger or smaller than expected
4. Outliers that are significantly higher or lower than the rest of the data
5. Trend changes or shifts that occur over time
6. Missing data points or gaps in the time series.
1. Spikes or sudden jumps in the data
2. Dips or sudden drops in the data
3. Seasonal fluctuations that are larger or smaller than expected
4. Outliers that are significantly higher or lower than the rest of the data
5. Trend changes or shifts that occur over time
6. Missing data points or gaps in the time series.
CFA考试视频What are the anomalies in the time series data？CFA一级视频
