Executed statistical analysis and data visualization in Python

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📅 2023-02-22 — Session: Executed statistical analysis and data visualization in Python

🕒 04:50–05:55
🏷️ Labels: Python, Statistics, Data Visualization, Parameter Sweeping
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The primary objective of this session was to perform statistical analysis and data visualization using Python. The focus was on calculating treatment differences, performing linear regression, and sweeping parameters for Average Treatment Effect (ATE) calculations.

Key Activities

  • Implemented a loop to calculate and print the mean and standard deviation of treatment differences (diff1 and diff2).
  • Executed linear regression on grouped data using SciPy, including error bars and printing the linear equation.
  • Plotted a line using Matplotlib based on the equation y = m*x + b.
  • Conducted parameter sweeping for ATE calculation, capturing mean and standard deviation for each parameter value.

Achievements

  • Successfully calculated statistical measures for treatment differences.
  • Completed linear regression analysis and visualization with error bars.
  • Generated plots using Matplotlib for visual representation of data.
  • Executed parameter sweeping for ATE calculations, ensuring robust statistical analysis.

Pending Tasks

  • Review and optimize the parameter sweeping code for efficiency.
  • Explore additional data visualization techniques to enhance clarity and presentation.

Graph View

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