About advanced statistics
The previous section shows you how to calculate basic statistics using
eval, and how to create sparkline charts.
In this section we discuss how to detect anomalies in your data. This could include finding outliers to identify anomalies or spikes in your data. You might want to remove outliers that unnecessarily skew your calculations or the way your charts plot the data. You can detect patterns in your data, grouping events based on how similar the events are to each other. If there are patterns and correlations to events that you monitor, you can use them to predict future activity. With this knowledge, you can proactively send alerts based on thresholds and perform "what-if" analyses to compare various scenarios. All of this and more is possible with advanced statistics.
- Commands for advanced statistics
- About anomaly detection
- Finding and removing outliers
- Detecting anomalies
- Detecting patterns
- About time series forecasting
- Machine Learning Toolkit
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Commands for advanced statistics
This documentation applies to the following versions of Splunk® Enterprise: 6.3.1, 6.3.2, 6.3.3, 6.3.4, 6.3.5, 6.3.6, 6.3.7, 6.3.8, 6.3.9, 6.3.10, 6.3.11, 6.3.12, 6.4.0, 6.4.1, 6.4.2, 6.4.3, 6.4.4, 6.4.5, 6.4.6, 6.4.7, 6.4.8, 6.4.9, 6.5.0, 6.5.1, 6.5.1612 (Splunk Cloud only), 6.5.2, 6.5.3, 6.5.4, 6.5.5, 6.5.6, 6.6.0, 6.6.1, 6.6.2, 6.6.3, 6.6.4, 7.0.0