Add comprehensive biomedical statistical tests with visualizations#286
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siriak merged 1 commit intoTheAlgorithms:masterfrom Oct 26, 2025
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Features: - Comprehensive T-Tests (one-sample, two-sample, paired, Welch's) with clinical examples - Chi-Square Tests (goodness of fit, independence, McNemar's) with medical applications - Correlation Analysis (Pearson, Spearman, Kendall, matrix analysis) with assumption checks - Professional visualizations for all tests with statistical annotations - Power analysis and sample size considerations for study design - Real-world biomedical examples and interpretations Files added: - biomedical/t_tests_comprehensive.r (800+ lines) - biomedical/chi_square_tests.r (700+ lines) - biomedical/correlation_analysis.r (600+ lines) - Updated DIRECTORY.md with new biomedical tests Testing: - All functions tested with and without plotting - Comprehensive error handling and input validation - Educational demonstrations with clinical scenarios - No external package dependencies (pure base R)
Brijesh03032001
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Panquesito7,
acylam and
siriak
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Pull Request Overview
This PR adds three comprehensive biomedical statistical test implementations with advanced visualizations to enhance the repository's biomedical analysis capabilities. The additions include comprehensive t-tests, chi-square tests, and correlation analysis methods.
Key Changes:
- Added three new statistical test implementations with educational demonstrations
- Implemented professional-quality visualizations for each test type
- Included power analysis and sample size calculations
Reviewed Changes
Copilot reviewed 4 out of 5 changed files in this pull request and generated 3 comments.
| File | Description |
|---|---|
| biomedical/t_tests_comprehensive.r | Implements one-sample, two-sample, paired, and Welch's t-tests with visualization and power analysis |
| biomedical/correlation_analysis.r | Provides Pearson, Spearman, and Kendall correlation methods with assumption checking and matrix analysis |
| biomedical/chi_square_tests.r | Contains goodness-of-fit, independence, and McNemar's tests with effect size measures |
| DIRECTORY.md | Updated to include the three new biomedical statistical test files |
gladlysmtn-ship-it
approved these changes
Nov 30, 2025
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@siriak @acylam @Panquesito7 Please see to this too, this is reallt awesome work. I am a machine learning researcher so I thought to add this here with the demo dataset.
🧬 Add Comprehensive Biomedical Statistical Tests with Advanced Visualizations
🚀 Overview
This PR introduces a complete suite of essential biomedical statistical tests with professional visualizations and clinical examples. All implementations are built with base R (no external dependencies) and include comprehensive educational demonstrations for biomedical research applications.
✨ Features Added
📊 Comprehensive T-Tests (
t_tests_comprehensive.r)🎯 Chi-Square Test Suite (
chi_square_tests.r)📈 Advanced Correlation Analysis (
correlation_analysis.r)📊 Visualization Features
🎨 Professional Statistical Plots
📋 Educational Demonstrations
Each implementation includes realistic biomedical examples:
🧪 Testing & Validation
✅ Comprehensive Test Suite
🔬 Real-World Applications
📁 Files Modified/Added
biomedical/t_tests_comprehensive.r➕ (800+ lines)biomedical/chi_square_tests.r➕ (700+ lines)biomedical/correlation_analysis.r➕ (600+ lines)DIRECTORY.md📝 (Updated with new biomedical tests)🎓 Educational Value
📚 Learning Features
📖 Documentation
🔬 Biomedical Research Applications
🏥 Clinical Studies
🧪 Laboratory Research
📊 Public Health
🎯 Key Advantages
💪 Robust Implementation
📈 Professional Quality
🚀 Impact on Repository
🌟 Enhanced Biomedical Section
Ready for Hacktoberfest! 🎃 This comprehensive biomedical statistics suite provides essential tools for medical research, clinical trials, and biomedical data analysis with professional visualizations and educational value.