Confidence Intervals
Confidence intervals help assess accuracy and quantify uncertainty in results from sampled datasets. When querying sum or count fields on adaptive datasets, you can request a confidence interval to understand the possible range around an estimate. For example, specifying a confidence level of 0.95
returns the estimate, along with the range of values that likely contains the true value 95% of the time.
- Supported datasets: Adaptive (sampled) datasets only.
- Supported fields: All
sum
andcount
fields. - Usage: Confidence
level
must be provided as a decimal between 0 and 1 (for example,0.90
,0.95
,0.99
). - Default: If no confidence level is specified, intervals are not returned.
The following example shows how to query a confidence interval and interpret the response.
To request a confidence interval, use the confidence(level: X)
argument in your query.
query SingleDatasetWithConfidence($zoneTag: string, $start: Time, $end: Time) { viewer { zones(filter: {zoneTag: $zoneTag}) { firewallEventsAdaptiveGroups( filter: {datetime_gt: $start, datetime_lt: $end} limit: 1000 ) { count avg { sampleInterval } confidence(level: 0.95) { count { estimate lower upper sampleSize } } } } }}
The response includes the following values:
estimate
: The estimated value, based on sampled data.lower
: The lower bound of the confidence interval.sampleSize
: The number of sampled data points used to calculate the estimate.upper
: The upper bound of the confidence interval.
In this example, the interpretation of the response is that, based on a sample of 40,054, the estimated number of events is 42,939, with 95% confidence that the true value lies between 42,673 and 43,204.
{ "data": { "viewer": { "zones": [ { "firewallEventsAdaptiveGroups": [ { "avg": { "sampleInterval": 1.0720277625205972 }, "confidence": { "count": { "estimate": 42939, "lower": 42673.44115335711, "sampleSize": 40054, "upper": 43204.55884664289 } }, "count": 42939 } ] } ] } }, "errors": null}
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