5. Alternative Methods for Calculating Pearson Correlation and Significance in Python
   Pearson correlation is a statistical measure that quantifies the linear relationship between two variables. It ranges from -1 to 1, where -1 indicates a perfect negative correlation
6. Calculating Percentiles with Python/NumPy: A Breakdown of Example Code
   Percentiles and Their Significance:Percentiles are statistical measures that divide a dataset into 100 equal parts.For example
7. When to Use np.mean() vs. np.average() for Calculating Averages in Python
   Functionality:np. mean() calculates the arithmetic mean along a specified axis of the array. The arithmetic mean is the sum of all the elements divided by the number of elements
8. Demystifying Multiple Linear Regression: Python Code with pandas, numpy, and statsmodels
   MLR is a statistical technique used to model the relationship between a continuous dependent variable (what you're trying to predict) and two or more independent variables (factors that influence the dependent variable). It's an extension of simple linear regression
9. Fitting Theoretical Distributions to Real-World Data with Python's SciPy
   This process involves finding a theoretical probability distribution (like normal, exponential, etc. ) that best describes the pattern observed in your actual data (empirical distribution). SciPy's scipy