I'm excited to introduce tea-tasting, a Python package for the statistical analysis of A/B tests
It features Student's t-test, Bootstrap, variance reduction using CUPED, power analysis, and other statistical methods.
tea-tasting supports a wide range of data backends, including BigQuery, ClickHouse, PostgreSQL, Snowflake, Spark, and more, all thanks to Ibis.
I consider it ready for important tasks and use it for the analysis of switchback experiments in my work.
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