📊 Statistics Basics — Learning with Python

A beginner-friendly introduction to summary statistics with Python.
This repo contains two Jupyter notebooks: one for exercises and one with full solutions.

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📂 Contents

• Demonstrations — guided notebook with explanations, prompts, and exercises.
• Solutions and Answers — full solutions notebook with worked-out answers.
• requirements.txt — minimal dependencies to run the notebooks.

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📝 Topics Covered

• Descriptive vs. Inferential statistics
• Data types: numeric, categorical, nominal, ordinal
• Measures of center: mean, median, mode
• Measures of spread: standard deviation, mean absolute deviation (MAD)
• Quartiles and interquartile range (IQR)
• Boxplots for visualization
• Mini-project: compare salaries and orders by department

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🚀 Getting Started

1. Clone the repo

   git clone https://github.com/yourusername/StatsCourse.git
   cd StatsCOurse

2. Install dependencies

   pip install -r requirements.txt

3. Launch Jupyter Notebook

   jupyter notebook

   (But you can use any IDE you want)

4. Open notebooks

   • Start with stats_basics_exercises.ipynb
   • Check your work with stats_basics_solutions.ipynb

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📸 Preview

The notebooks include:

• Hands-on Python with NumPy and Pandas
• Visualizations with Matplotlib
• Short reflections to reinforce learning

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🙌 Contributing

Suggestions and improvements are welcome!
Feel free to open an issue or submit a pull request.

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⭐ Acknowledgements

Created as part of my learning journey through the
DataCamp Associate Data Scientist Certificate.