This repository is dedicated to storing and sharing applied regression analysis projects using R. It includes various scripts, datasets, and documentation to help understand and perform regression analysis in R. The goal is to provide a comprehensive resource for learning and applying regression techniques in real-world scenarios.
- R: R scripts that demonstrate different regression techniques, including linear regression, multiple regression, logistic regression, and more. Each script is well-documented to explain the steps and logic used.
- data: A collection of datasets used in the analysis. These datasets are either sourced from publicly available data or generated for educational purposes.
- docs: Documentation explaining the concepts of regression analysis, the methodology used in the scripts, and the interpretation of results. This includes markdown files and Jupyter notebooks with embedded R code.
- Educational Resource: To serve as a learning tool for students and professionals interested in regression analysis using R.
- Practical Application: To provide practical examples and use cases of regression analysis in various fields such as economics, biology, engineering, and social sciences.
- Collaboration: To encourage collaboration and contributions from the community to enhance the repository with new techniques, datasets, and improvements.
To get started with the repository, clone it to your local machine using the following command:
git clone https://github.com/Syarmine/applied-regression-analysis
Navigate to the directory and explore the contents. You can start with the README.md file for an overview and then proceed to the scripts and data folders for specific examples and data.
Contributions are welcome! If you have any improvements, new techniques, or datasets to add, please fork the repository and submit a pull request. Make sure to follow the contribution guidelines outlined in the CONTRIBUTING.md file.
This project is licensed under the MIT License. See the LICENSE file for more details.
We hope you find this repository useful and informative. Happy analyzing!