AI Statistics Activities

This repository contains all the activities completed during the statistics module of the Advanced Artificial Intelligence in Data Science I class. All activities were implemented using Jupyter Notebook with Python.

Activities

1. Linear Regression 1
2. Linear Regression 2
3. Classification Algorithms
4. Parameter Estimation
5. t-Student Distribution

Corrections Made

The following corrections were made based on previous feedback from the teacher:

Activity: Parameter Estimation

• The probability calculation has been adjusted as follows: p = n / n.sum() to obtain a result of 0.2977.

Activity: t-Student Distribution

• Corrections were made in the conclusions of the results. If p-value <= 0.05, the null hypothesis is rejected.
• The QQ-plot graphs were adjusted to a "45-degree" line instead of an "s" line.

Libraries Used

The following Python libraries were utilized for these activities:

• Pandas
• NumPy
• Matplotlib
• Scikit-learn
• Statsmodels
• SciPy
• math