This repository contains a simple example of post-experiment analysis and power analysis.
In this section, we provide a simple example of post-experiment from open-source data. source data here.
To view the detailed post-experiment analysis, click here.
Power analysis is an important aspect of experimental design that helps determine the sample size required to detect a specific effect with a given level of confidence. In the code, we show how to calculate the power analysis, especially for proportion metrics. For another type of metrics, we can change the value of variance of the metrics.
To view the detailed power analysis, click here.
Feel free to explore the analysis and calculations provided in each section for a better understanding of post-experiment analysis and power analysis concepts.
We welcome any feedback, suggestions, or contributions you may have. Please feel free to open an issue or submit a pull request.