https://github.com/qtle3/stats

This repository contains two Python scripts, `stats_calculations.py` and `stats_user.py`, which provide a comprehensive toolset for performing statistical calculations. The program allows users to compute various statistical metrics such as mean, median, mode, variance, and standard deviation, all through a user-friendly command-line interface.
https://github.com/qtle3/stats

alogrithm error-handling modular-design python-functions quick-select statistical-analysis user-input

Last synced: about 1 month ago
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This repository contains two Python scripts, `stats_calculations.py` and `stats_user.py`, which provide a comprehensive toolset for performing statistical calculations. The program allows users to compute various statistical metrics such as mean, median, mode, variance, and standard deviation, all through a user-friendly command-line interface.

• Host: GitHub
• URL: https://github.com/qtle3/stats
• Owner: qtle3
• Created: 2024-08-02T03:48:39.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2024-08-02T04:43:39.000Z (10 months ago)
• Last Synced: 2025-02-14T16:01:52.660Z (3 months ago)
• Topics: alogrithm, error-handling, modular-design, python-functions, quick-select, statistical-analysis, user-input
• Language: Python
• Homepage:
• Size: 6.84 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
## Scripts

### 1. `stats_calculations.py`

- **Purpose:** Provides functions to perform statistical calculations.

- **Key Functions:**

  - `calculate_mean()`: Computes the average of a list of numbers.

  - `calculate_median()`: Determines the middle value in a sorted list.

  - `calculate_mode()`: Finds the most frequent value in a list.

  - `calculate_variance()`: Measures the dispersion of a set of numbers.

  - `calculate_standard_deviation()`: Calculates the amount of variation in a dataset.

  - `calculate_quartiles()`: Computes the quartiles of a dataset.

  - `get_numbers_from_user()`: Handles user input for numbers.

  

### 2. `stats_user.py`

- **Purpose:** Provides a command-line interface (CLI) for interacting with statistical functions.

- **Features:**

  - Interactive menu for selecting statistical operations.

  - Data visualization using histograms.

  - Allows for repeated calculations without restarting the program.

 

## Key Concepts Covered

- **Statistical Analysis:** Understand and compute basic statistical measures.

- **Python Functions:** Modularize code using functions for different calculations.

- **Error Handling:** Manage user input and handle exceptions gracefully.

- It also includes a `quick_select` algorithm for efficient median calculation.