---
metadata:
  - name: generator
    content: Diplodoc Platform v5.57.3
alternate:
  - https://yandex.com/support/varioqub/en/stat/bayes.md
  - https://yandex.com/support/varioqub/ru/stat/bayes.md
  - https://yandex.com/support/varioqub/tr/stat/bayes.md
  - href: https://yandex.com/support/varioqub/en/stat/bayes.md
    type: text/markdown
    title: Markdown version
  - href: https://yandex.com/support/varioqub/en/llms.txt
    type: text/markdown
    title: llms.txt
---
> **Documentation Index:** Fetch the complete configuration index at https://yandex.com/support/varioqub/en/llms.txt

# Calculating metrics using the Bayesian method

To calculate [conversions to goals](https://yandex.com/support/varioqub/en/stat.md#bayes), Varioqub employs the Bayesian method. The Bayesian method helps calculate the probability of the rate of user conversion to a certain goal being higher for the test group rather than for the control group.

The probability is calculated by the following formula:

$P(\lambda_T > \lambda_C​ ​) = sum_{i=0}^{\alpha_T - 1} \exp(logBeta(\alpha_C + i,\beta_C + \beta_T) - \log(\beta_T + i) - logBeta(1 + i, \beta_T) - logBeta(\alpha_C, \beta_C) )$
where $logBeta(x,y) = logGamma(x) + logGamma(y) - logGamma(x+y)$.

The probability is displayed in the experiment results report: **Probability test > control**. If the calculation shows that the test variant is better than the control one, it's highlighted in green. If it's worse, it's highlighted in red.

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