github.com/talaamm/math-skills_april2024

README.md

Math Skills

This repository contains Math Skills, a program that calculates essential statistical measures: average, median, variance, and standard deviation. The program reads numerical data from a file and outputs the computed statistics.

This project was independently implemented by me and served as an opportunity to improve my programming and mathematical skills.

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Features

The program computes the following statistical measures:

1. Average
   The arithmetic mean of the dataset.

   • Example: For values 1, 2, 3, 4, 5, the average is 3.

2. Median
   The middle value of the dataset when sorted.

   • Example: For 1, 3, 5, 7, 9, the median is 5.
     If the dataset has an even number of elements, the median is the average of the two middle values.

3. Variance
   The measure of dispersion, calculated as the average of the squared differences from the mean.

4. Standard Deviation
   The square root of the variance, indicating how much the values deviate from the mean.

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Usage

Input File Format

• The input file must contain one numeric value per line.
  Example (data.txt):

  189
  113
  121
  114
  145
  110
  

Running the Program

To execute the program, provide the path to the data file as an argument.

$ go run math-skills.go <data_file>

Example Output

For a file (data.txt) containing:

10
20
30
40
50

The output will be:

Average: 30
Median: 30
Variance: 200
Standard Deviation: 14

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What I Learned

• File Operations: Reading data from files and handling potential errors.
• Mathematical Concepts: Implementing core statistical functions programmatically.
• Sorting Algorithms: Using sorting to determine the median efficiently.
• Precision and Rounding: Managing numerical computations and rounding results to integers.

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Future Enhancements

• Add support for floating-point precision outputs.
• Implement additional statistical measures like mode and range.
• Handle datasets with missing or invalid data gracefully.

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Acknowledgments

This project was my first step into blending programming with statistical analysis. It was a rewarding challenge that enhanced both my coding and mathematical problem-solving abilities.