abalytics 1.0.0

An A/B test analysis package.

# Abalytics

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. P