Welcome to prayas!

Prayas is a Bayesian A/B Testing framework written in Python and used within Avira to make business decisions in many different areas.

Controlled experiments (A/B tests or randomized field experiments) are the de facto standard to make data-driven decisions when implementing changes and observing customer responses. Bayesian inference allows us to express the results in easy to understand measures like probability to be the best variant and expected uplift in conversion rates.

The prayas package currently implements three experiment scenarios that are common in our company:

1. One option model – A variant contains only one option to select

2. Multi-options model – A variant can contain more than one option to select

3. Aggregated model – Per variant only aggregated measures are observed

See Examples for an illustration of each model. The underlying methodology is described in Bayesian A/B Testing for Business Decisions by Shafi Kamalbasha and Manuel J. A. Eugster (2020).

Contents

• Getting started
• Examples
  • One option model
  • Multi-options model
  • Aggregated model
  • One option vs. multi-options model
  • Experiments
• Modules
  • Module model_conversion
  • Module model_oneoption
  • Module model_multioptions
  • Module model_aggregate
  • Module experiment

Version

Documentation based on prayas version 0.1; generated on Nov 27, 2020.

Feedback

In case of any bug, comments, feature requests, etc. please open an issue on the project Github page.

Contributors

• Shafi Kamalbasha

• Alin Secareanu

• Manuel Eugster

License

MIT License. Copyright (c) 2019-2020 Avira Operations GmbH & Co. KG