Automate statistical validation, hypothesis testing, and confidence interval calculations required by TAR UMT thesis standards and top ML research conferences. Use when you need to (1) calculate 95% confidence intervals for model performance metrics, (2) perform hypothesis testing to compare models (McNemar's test, paired t-test, Bonferroni correction), (3) generate APA-formatted results tables for thesis chapters, (4) create reproducibility statements for experimental setup, (5) validate statistical significance of model improvements, or (6) format results according to academic publishing standards. Essential for FYP Chapter 4 (experimental setup documentation) and Chapter 5 (results with statistical validation).
Key Features
- Comprehensive skill evaluation and performance tracking
- Community-driven ratings and reviews
- Easy integration with Claude Code
- Regular updates and maintenance
Quick Start
TopRank Skills install Ming-Kai-LC/fyp-statistical-validator
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