Statistics Calculator 📊

A command-line statistics calculator that computes essential statistical measures from a list of numbers. Built with Node.js using functional programming principles and array methods to calculate mean, median, mode, range, variance, and standard deviation.

📖 About The Project

This CLI application takes a comma-separated list of numbers and calculates six fundamental statistical measures, displaying each result with a clear explanation of what it means. Perfect for students learning statistics, data analysts needing quick calculations, or developers practicing functional programming.

Statistical Measures Calculated

• Mean - The average of all numbers
• Median - The middle value when numbers are sorted
• Mode - The most frequently occurring number(s)
• Range - The difference between largest and smallest values
• Variance - How spread out the numbers are from the mean
• Standard Deviation - The square root of variance (measure of dispersion)

✨ Features

• 📈 Six Statistical Measures - Comprehensive descriptive statistics
• 🎨 Colorful Output - Using Chalk for enhanced readability
• 📚 Educational Explanations - Each statistic comes with a clear definition
• 🔢 Handles Multiple Modes - Displays all modes when multiple exist
• ✅ No Mode Detection - Returns null when all values appear equally
• 🎯 Functional Programming - Uses map, reduce, filter, forEach
• 💯 Accurate Calculations - Implements correct statistical formulas
• 🖥️ Clean CLI Interface - Simple input, formatted output

📸 Demo

$ node app.mjs

Enter a list of comma-seperated numbers
Numbers: 2, 4, 6, 8, 10

Mean: 6
The mean of a list of numbers is the average, calculated by taking the sum 
of all numbers and dividing that by the count of numbers.

Median: 6
The median of a list of numbers is the number that appears in the middle 
of the list, when sorted from least to greatest.

Mode: null
The mode of a list of numbers is the number that appears most often in the list.

Range: 8
The range of a list of numbers is the difference between the largest and 
smallest numbers in the list.

Variance: 8
The variance of a list of numbers measures how far the values are from 
the mean, on average.

Standard Deviation: 2.8284271247461903
The standard deviation of a list of numbers is the square root of the variance.

Example with Mode

Numbers: 1, 2, 2, 3, 3, 3, 4, 5

Mean: 2.875
Median: 3
Mode: 3
Range: 4
Variance: 1.609375
Standard Deviation: 1.2686370808172522

Example with Multiple Modes

Numbers: 1, 1, 2, 3, 3, 4

Mean: 2.3333333333333335
Median: 2.5
Mode: 1, 3
Range: 3
Variance: 1.2222222222222223
Standard Deviation: 1.1055415967851332

🛠️ Built With

• Node.js - JavaScript runtime environment
• ES6 Modules (.mjs) - Modern JavaScript syntax
• prompt-sync - Synchronous user input
• chalk - Terminal string styling and colors
• Functional Programming - Array methods (map, reduce, filter, forEach)

📋 Prerequisites

• Node.js (v12.0.0 or higher)
• npm (Node Package Manager)

Check your installation:

node --version
npm --version

🚀 Installation & Setup

1. Clone the Repository

git clone https://github.com/rishiverma12031/StatisticsCalculator.git
cd StatisticsCalculator

2. Install Dependencies

npm install prompt-sync chalk

3. Run the Calculator

node app.mjs

💻 Usage

1. Run the application: node app.mjs
2. Enter numbers separated by commas when prompted
   • Example: 2, 4, 6, 8, 10
   • Spaces are automatically trimmed
3. View all statistics displayed with explanations

Input Format

• Comma-separated numbers: 1, 2, 3, 4, 5
• Decimals supported: 1.5, 2.7, 3.9
• Spaces optional: 1,2,3 or 1, 2, 3 both work
• Negative numbers: -5, -2, 0, 3, 7

📁 Project Structure

StatisticsCalculator/
│
├── app.mjs              # Main application file
├── package.json         # Project dependencies (create this)
└── README.md           # Documentation

🔧 Code Structure & Algorithms

Main Functions

calculateMean(numbers)

const mean = numbers.reduce((sum, currentNumber) => sum += currentNumber, 0) / numbers.length;

• Uses reduce() to sum all numbers
• Divides by count for average

calculateMedian(numbers)

const sortedNumbers = numbers.slice().sort((a, b) => a - b);

• Sorts numbers in ascending order
• For even count: Average of two middle values
• For odd count: Middle value

calculateMode(numbers)

const numbersWithCount = {};
numbers.forEach(number => numbersWithCount[number] = (numbersWithCount[number] || 0) + 1);

• Creates frequency map using object
• Finds maximum frequency
• Returns all numbers with max frequency
• Returns null if all frequencies are equal

calculateRange(numbers)

const range = Math.max(...numbers) - Math.min(...numbers);

• Uses spread operator with Math.max/min
• Calculates difference

calculateVariance(numbers)

const squaredDeviations = numbers.map(deviation => (deviation - mean) ** 2);
const variance = calculateMean(squaredDeviations);

• Calculates squared deviations from mean
• Takes mean of squared deviations

calculateStandardDeviation(numbers)

const standardDeviation = Math.sqrt(variance);

• Square root of variance

🎓 Learning Outcomes

This project demonstrates mastery of:

JavaScript Concepts

• ✅ Array Methods - map, reduce, filter, forEach, slice, sort
• ✅ Functional Programming - Pure functions, no side effects
• ✅ Object Manipulation - Creating frequency maps
• ✅ Spread Operator - Used with Math.max/min
• ✅ Arrow Functions - Concise function syntax
• ✅ Template Literals - String interpolation
• ✅ Ternary Operators - Conditional expressions
• ✅ Set Data Structure - Checking unique values

Mathematical Concepts

• Descriptive statistics formulas
• Measures of central tendency (mean, median, mode)
• Measures of dispersion (range, variance, standard deviation)
• Data analysis fundamentals

Programming Practices

• Clean code organization
• Function reusability (variance uses mean)
• Input parsing and data transformation
• Educational output with explanations

🧮 Statistical Formulas Explained

Mean (Average)

Mean = (Sum of all numbers) / (Count of numbers)

Median (Middle Value)

If count is odd: Middle element of sorted array
If count is even: Average of two middle elements

Mode (Most Frequent)

The value(s) that appear most frequently
If all values appear equally: No mode (null)

Range (Spread)

Range = Maximum value - Minimum value

Variance (Dispersion)

Variance = Mean of squared deviations from the mean
= Average of [(x₁ - mean)², (x₂ - mean)², ..., (xₙ - mean)²]

Standard Deviation

Standard Deviation = √Variance

🧪 Test Cases

Try these datasets to test the calculator:

Dataset	Mean	Median	Mode	Range	Variance	Std Dev
2, 4, 6, 8, 10	6	6	null	8	8	2.83
1, 1, 2, 3, 3, 3	2.17	2.5	3	2	0.81	0.90
5, 5, 5, 5, 5	5	5	null	0	0	0
1, 2, 3, 4, 5, 6, 7, 8, 9, 10	5.5	5.5	null	9	8.25	2.87
10, 20, 30, 40, 50	30	30	null	40	200	14.14

Edge Cases

• All same numbers: Mean = Median = number, Mode = null, Range = 0, Variance = 0
• Two numbers: Median = average of both
• Bimodal dataset: Mode shows multiple values (e.g., "1, 3")

🎨 Customization Ideas

Easy Modifications

• Add formatting to limit decimal places
• Color-code statistics by type
• Add data visualization with ASCII charts
• Include count of numbers in output

Medium Challenges

• Add quartiles (Q1, Q2, Q3)
• Calculate percentiles
• Add skewness and kurtosis
• Support reading from CSV files
• Add histogram display

Advanced Features

• Create data visualization charts
• Add correlation analysis for two datasets
• Support multiple datasets comparison
• Build a web interface
• Add statistical significance tests
• Export results to file

🐛 Troubleshooting

Common Issues

Error: "Cannot find module 'prompt-sync'"

npm install prompt-sync

Error: "Cannot find module 'chalk'"

npm install chalk

NaN or undefined results

• Ensure input contains only numbers separated by commas
• Check for proper number formatting

Incorrect median calculation

• The code properly handles both even and odd length arrays
• Uses slice() to avoid mutating original array

🎨 Color Scheme

The application uses Chalk for colored output:

• 🟣 Magenta - Input prompt
• 🟢 Green - User input field
• 🔷 Cyan (Bold) - Statistical results
• ⚪ White - Explanatory text

🌟 Future Enhancements

Planned features:

• Add more statistics (quartiles, IQR, skewness, kurtosis)
• Support file input (CSV, JSON)
• Add data visualization (histograms, box plots)
• Export results to file
• Batch processing of multiple datasets
• Web interface version
• Add confidence intervals
• Support weighted statistics
• Include hypothesis testing
• Add correlation and regression analysis

🤝 Contributing

Contributions are welcome! Here's how:

1. Fork the project
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Ideas for contributions:

• Add more statistical measures
• Improve input validation
• Add unit tests
• Create data visualization
• Add export functionality

📝 License

This project is open source and available under the MIT License.

👤 Author

Rishi Verma

• GitHub: @rishiverma12031
• Project Link: https://github.com/rishiverma12031/StatisticsCalculator

🙏 Acknowledgments

• Built to practice functional programming and array methods
• Uses prompt-sync for user input
• Uses chalk for terminal colors
• Implements standard statistical formulas and methods

📚 Resources & References

• Statistics Fundamentals - Khan Academy
• MDN - Array Methods
• Descriptive Statistics
• Standard Deviation Explained

💡 Educational Note

This calculator implements statistical formulas from scratch using JavaScript array methods and functional programming. While libraries like Math.js or simple-statistics exist, building from scratch helps understand:

• How statistical calculations work
• Functional programming patterns
• Array method applications
• Mathematical algorithm implementation

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Ready to calculate? Run node app.mjs and enter your data! 📊

Built with ❤️ while learning functional programming and statistics in JavaScript