This Streamlit app allows you to simulate A/B tests for evaluating the performance of different versions of a web page or application. It generates synthetic data for A/B testing based on user-defined parameters and provides various statistical analyses and visualizations to interpret the results.
- Data Generation Model: Customize the parameters for generating synthetic data including base click-through rate (CTR), CTR uplift, skewness, and beta distribution parameters.
- Experiment Design: Specify the significance level, power, and minimum detectable effect to design your A/B tests.
- Ground Truth Distributions: Visualize the distributions of CTR and views for control and treatment groups under the null and alternative hypotheses.
- A/B Tests Results: Conduct various statistical tests including t-tests, Mann-Whitney U tests, and binomial tests to compare the performance of control and treatment groups. Visualize the distributions and empirical cumulative distribution functions (CDFs) of p-values.
- Statistical Power Analysis: Evaluate the statistical power of the conducted tests to detect significant differences between groups.
- Data Generation Model: Adjust the sliders in the sidebar to customize the parameters for generating synthetic data.
- Experiment Design: Set the significance level, power, and minimum detectable effect for designing your A/B tests.
- Click "Apply" to generate the synthetic data and estimate the parameters.
- Review Ground Truth Distributions: Examine the distributions of CTR and views under the null and alternative hypotheses.
- Conduct A/B Tests: Explore the results of various statistical tests and visualizations.
- Interpret Results: Analyze the p-value distributions and statistical power to draw conclusions about the effectiveness of the tested variations.
To run this Streamlit app locally, follow these steps:
- Clone this repository:
git clone https://github.com/insdout/AB-test-simulator.git
- Navigate to the project directory:
cd AB-test-simulator
- Install the required dependencies:
pip install -r requirements.txt
- Run the Streamlit app:
streamlit run streamlit_app.py
- Access the app in your web browser at http://localhost:8501.