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Quantitative Analysis: Input Device Comparison

Python Pandas Matplotlib

🎯 Project Overview

This project aims to compare the performance and usability of two different input devices (Eingabegerät A and Eingabegerät B). Using a dataset of study results, the script generates statistical visualizations to identify trends and performance gaps.

📊 Visualizations

Boxplot Comparison

🔍 Statistical Analysis & Results

Based on the generated boxplot, the study reveals significant differences:

  • Central Tendency (Median): Eingabegerät A (Median ≈ 2.0) performed significantly better than Eingabegerät B (Median ≈ 4.5).
  • Data Spread (Variance): Eingabegerät B has a much larger Interquartile Range (IQR), indicating that user performance was inconsistent and highly variable.
  • Range: * Eingabegerät A: Results are tightly clustered between 1.0 and 4.0.
    • Eingabegerät B: Results are widely dispersed, ranging from 2.0 to 7.0.
  • Conclusion: Eingabegerät A is the more efficient and reliable device for this task, producing lower values with higher consistency.

🛠️ Tech Stack

  • Language: Python 3.12.2
  • Libraries: Pandas, Matplotlib

📖 How to Run

1.Clone the repository: git clone https://github.com/demgn/Quantitative_analyse.git 2. Install dependencies: pip install pandas matplotlib 3. Ensure you have the data file study_results.csv in the root folder. 4. Run the script: python main.py


Developed as part of my Software Engineering studies @ University of Duisburg-Essen.

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Quantitative analysis and visualization of user performance across two different input devices.

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