A basic comparison of different statistical methods for data understanding and exploration.
This repository contains a project that focuses on performing basic statistical comparisons between datasets. The project aims to explore and analyze different statistical measures to gain insights and make informed decisions based on the data.
- Implements various statistical measures such as mean, median, mode, variance, and standard deviation
- Conducts statistical comparisons between datasets using hypothesis testing techniques
- Provides a user-friendly interface for interacting with the project
- Python 3.x
- NumPy
- Pandas
- SciPy
- Clone the repository:
git clone https://github.com/your-username/stats-comparison-project.git - Navigate to the project directory:
cd stats_comparison_project - Install the required dependencies:
pip install -r requirements.txt
- Prepare your datasets in a suitable format, ensuring they contain the necessary variables for comparison.
- Open the Jupyter Notebook or Python script containing the project code.
- Customize the code as needed, such as updating the file paths or selecting the statistical measures to compute.
- Execute the code to perform statistical comparisons and generate visualizations.
- Analyze the results, interpret the statistical measures, and draw conclusions based on the comparisons.
Contributions are welcome! If you encounter any issues or have suggestions for improvement, please feel free to submit a pull request or open an issue.
This project is licensed under the MIT License.
This project was inspired by the need to compare and analyze datasets using statistical measures. I acknowledge the contributions of the open-source community and various libraries used in this project.