Developed Statistical Analysis and Visualization in Python

📅 2023-02-22 — Session: Developed Statistical Analysis and Visualization in Python

🕒 04:55–05:55
🏷️ Labels: Python, Data Analysis, Visualization, Statistics, ATE
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to enhance statistical analysis and data visualization techniques using Python, focusing on treatment differences and parameter sweeping for Average Treatment Effect (ATE) calculations.

Key Activities

• Implemented a loop to calculate and print the mean and standard deviation of treatment group differences (diff1 and diff2).
• Performed linear regression on grouped data using SciPy, including error bars and printing the linear equation.
• Used Matplotlib to plot lines based on linear equations (y = m*x + b).
• Conducted parameter sweeping to calculate ATE, capturing mean and standard deviation results.

Achievements

• Successfully executed statistical analysis of treatment differences.
• Developed and visualized linear regression models with error bars.
• Implemented parameter sweeping for ATE calculations, enhancing data analysis capabilities.

Pending Tasks

• Further exploration of parameter impacts on ATE results could be beneficial for deeper insights.