Configure Variance Reduction

Variance reduction uses pre-exposure data to reduce noise in your experiment metrics. This allows you to detect effects with fewer samples or detect smaller effects with the same sample size.

How It Works

The Stats API applies regression adjustment to reduce variance. You provide pre-exposure measurements alongside your post-exposure data, and the API uses the correlation between them to produce more precise estimates.

Configure Variance Reduction for Analysis

Include pre-exposure data in the adjustment field within your summary data:

{
  "id": "my-metric",
  "segments": [
    {
      "dimensions": {},
      "groups": [
        {
          "group": "control",
          "data": {
            "zTest": {
              "summary": {
                "mean": 10.5,
                "variance": 25.0,
                "count": 1000,
                "adjustment": {
                  "mean": 9.8,
                  "variance": 22.0,
                  "covariance": 15.2
                }
              }
            }
          }
        },
        {
          "group": "treatment",
          "data": {
            "zTest": {
              "summary": {
                "mean": 11.2,
                "variance": 26.0,
                "count": 1000,
                "adjustment": {
                  "mean": 9.9,
                  "variance": 21.5,
                  "covariance": 14.8
                }
              }
            }
          }
        }
      ]
    }
  ]
}

Adjustment Fields

The adjustment object contains:

Field	Description
`mean`	Mean of the pre-exposure measurements
`variance`	Variance of the pre-exposure measurements
`covariance`	Covariance between pre-exposure and post-exposure values