https://github.com/shaadclt/statistics-python
This project provides a collection of Jupyter Notebook exercises for practicing statistics concepts using Python. Statistics is a fundamental field in data analysis and plays a crucial role in understanding and interpreting data. Through this project, we aim to enhance our statistical skills by implementing various concepts using Python.
https://github.com/shaadclt/statistics-python
Last synced: 2 months ago
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This project provides a collection of Jupyter Notebook exercises for practicing statistics concepts using Python. Statistics is a fundamental field in data analysis and plays a crucial role in understanding and interpreting data. Through this project, we aim to enhance our statistical skills by implementing various concepts using Python.
- Host: GitHub
- URL: https://github.com/shaadclt/statistics-python
- Owner: shaadclt
- Created: 2022-10-19T06:16:18.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2023-07-08T10:33:08.000Z (about 2 years ago)
- Last Synced: 2025-04-09T17:01:52.228Z (6 months ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 798 KB
- Stars: 4
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Statistics Concepts Practice using Python
This project provides a collection of Jupyter Notebook exercises for practicing statistics concepts using Python. Statistics is a fundamental field in data analysis and plays a crucial role in understanding and interpreting data. Through this project, we aim to enhance our statistical skills by implementing various concepts using Python and gaining hands-on experience with real-world datasets.
## Prerequisites
Before running the code, make sure you have the following dependencies installed:
- Python (3.x)
- Jupyter Notebook
- Pandas
- NumPy
- Matplotlib
- SciPy
- StatsModels
## Getting Started
To get started with the project, follow the steps below:
1. Clone the repository:
```bash
git clone https://github.com/shaadclt/Statistics-Python.git
```
2. Change into the project directory:
```bash
cd Statistics-Python
```
3. Install the required dependencies:
4. Run Jupyter Notebook:
```bash
jupyter notebook
```
5. Open the Jupyter Notebook files (*.ipynb) in Jupyter.
6. Follow the instructions in the notebooks to practice and explore different statistics concepts using Python.
## Project Overview
The project covers various statistics concepts, including but not limited to:
1. Descriptive Statistics: Computing measures such as mean, median, mode, variance, and standard deviation.
2. Probability Distributions: Working with different probability distributions, such as normal, binomial, or Poisson distributions.
3. Correlation and Regression: Exploring relationships between variables and performing linear regression analysis.
Each notebook includes code snippets, and practice exercises to reinforce the understanding of statistics concepts using Python.
## Results and Insights
The emphasis of this project is on practicing and implementing statistics concepts rather than providing specific results or insights. Each notebook contains exercises and examples to apply the concepts learned and gain a deeper understanding of statistical analysis using Python. Feel free to experiment with different datasets, modify the exercises, or explore additional statistical concepts beyond the provided exercises.
## Customization
You can customize the project by adding your own datasets, creating additional notebooks for specific topics, or expanding the exercises with more advanced statistical concepts. This project serves as a starting point for you to practice and enhance your statistical skills using Python.
## License
This project is licensed under the MIT License. See the `LICENSE` file for more information.
## Acknowledgments
- This project is created for the purpose of practicing statistics concepts using Python and Jupyter Notebook.
## Contributing
Contributions are welcome! If you find any issues, have suggestions for improvements, or want to add more exercises, please open an issue or submit a pull request.