Welcome to the "Data Analysis" repository. This collection of Jupyter Python notebooks covers various aspects of data analysis, providing insights into statistical techniques and probability concepts.

1. Bayesian Probability.ipynb: Explore Bayesian probability and its applications in data analysis.

2. Correlation Coefficient Matrix.ipynb: Understand and compute the correlation coefficient matrix for multiple variables.

3. Histogram Bins.ipynb: Learn about the importance of choosing appropriate histogram bins in data visualization.

4. Kolmogorov-Smirnov Test.ipynb: Implement and interpret the Kolmogorov-Smirnov test for assessing the goodness-of-fit of a sample distribution.

5. Moments of Distribution.ipynb: Calculate and analyze moments of a distribution to understand its shape and characteristics.

6. PDF Gaussian.ipynb: Dive into the Probability Density Function (PDF) of a Gaussian distribution.

Feel free to explore each notebook to deepen your understanding of data analysis concepts and statistical techniques.

To run these Jupyter notebooks, ensure you have Python and Jupyter installed on your system. You can install Jupyter using:

pip install jupyter

Navigate to the specific notebook's file and execute the following command:

jupyter notebook notebook_name.ipynb

Replace notebook_name.ipynb with the desired notebook's file name.

Happy analyzing! 📊📈