abalytics 1.1.3

An A/B test analysis package.

ABalytics: Advanced A/B Testing Statistical Analysis

ABalytics is a Python package designed for statistical analysis, particularly for assessing the significance of A/B testing results. Its goal is to provide high-quality analysis by selecting the appropriate statistical tests based on the type of variable being analyzed. It offers a suite of tools to perform various significance tests and posthoc analyses on experimental data.

Features

• Boolean and Numeric Analysis: Supports analysis of both boolean and numeric data types, ensuring the use of correct statistical methods for each.
• Significance Tests: Includes a variety of significance tests such as Chi-Square, Welch's ANOVA, and Kruskal-Wallis, to accurately determine the significance of results.
• Posthoc Analysis: Offers posthoc analysis methods like Tukey's HSD, Dunn's test, and Games-Howell, for detailed examination following significance tests.
• Normality and Homogeneity Checks: Performs checks for Gaussian distribution and homogeneity of variances using Levene's test, which are critical for selecting the right tests.
• Pretty Text Output: Generates a formatted text output with the results of the statistical tests, facilitating interpretation and reporting.

Installation

To install ABalytics, use pip: pip install abalytics

Usage

To use ABalytics, import it: import abalytics

An example of how to use ABalytics can be found in examples/example.py.

Contributing

Contributions to ABalytics are welcome.