https://github.com/samcole8/degree-calculator

A Python-based degree calculator with some useful statistics.
https://github.com/samcole8/degree-calculator

calculator degree degree-classification monte-carlo probability-distribution

Last synced: about 2 months ago
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A Python-based degree calculator with some useful statistics.

• Host: GitHub
• URL: https://github.com/samcole8/degree-calculator
• Owner: samcole8
• License: gpl-3.0
• Created: 2025-07-17T17:25:20.000Z (3 months ago)
• Default Branch: master
• Last Pushed: 2025-07-17T20:21:52.000Z (3 months ago)
• Last Synced: 2025-08-10T19:50:10.460Z (2 months ago)
• Topics: calculator, degree, degree-classification, monte-carlo, probability-distribution
• Language: Python
• Homepage:
• Size: 77.1 KB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
## degree-calculator

[![Release](https://img.shields.io/github/v/release/samcole8/degree-calculator)](https://github.com/samcole8/degree-calculator/releases/latest)

![License](https://img.shields.io/badge/license-GPL--3.0-blue)

![Repo Size](https://img.shields.io/github/repo-size/samcole8/degree-calculator)

A Python-based degree award calculator with some useful (and some questionably useful) statistics.

![Histogram showing simulated grade distribution](resources/final_grade_distribution.png)

### Usage guide

1. Install Python and clone/download this repository.

2. Create a `units.yml` file by copying the [example](degree-calculator/units.example.yml)

3. Enter information about your degree units/modules (ideally including all future ones for accurate results)

4. Optionally, add information about your degree classification thresholds for extra statistics.

### Outputs

1. **Weighted averages**  

    

    Calculates each unit's predicted grade using appropriately weighted existing assessment marks. Then, computes the weighted average across all units to provide a predicted final grade and classification.

2. **Minimum/actual grade calculation**

    Calculates the weighted final grade using only existing grades, assuming missing grades are zero.

3. **Maximum grade calculation**

    Calculates the weighted final grade and classification using existing grades, while assuming missing grades are perfect scores (100%).

4. **Probabilistic Prediction**

    Calculates variance and weighted means based on existing grades, then uses the Monte Carlo method to simulate unknown units. Provides the following statistics:

    - **Median**: Another estimate for final grade and classification.

    - **5th & 95th percentiles**: Upper and lower bounds to guage distribution of results.

    - **Simulated probabilities of classifications**: Estimated probabilities of achieving the provided classifications.

    - **Histogram**: A histogram illustrating the distribution of simulated units.