iramler/slu_score_module_development
May 2025 – Jun 2025
2 Months active
Languages Used
HTMLMarkdownR
Technical Skills
CalculusData AnalysisData VisualizationFront End DevelopmentNon-linear RegressionR Programming
jchapmanSLU
PROFILE
Jchapmanslu
During their two-month tenure, Chapman contributed to the iramler/slu_score_module_development repository by first streamlining reviewer workflows through targeted documentation cleanup, removing obsolete forms to improve repository hygiene and future maintainability. In the following month, Chapman overhauled the Powerlifting module’s nonlinear regression workflow, applying R programming and statistical modeling to enhance age versus deadlift growth-decay analysis. This included updating dataset references, refining growth-decay curve visualizations, and implementing calculus-based derivations with bootstrap confidence intervals for peak performance estimation. Chapman’s work demonstrated depth in data analysis and front end development, resulting in more accurate, reproducible analytics and clearer instructional materials for end users.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
6Total
Bugs
0
Commits
6
Features
2
Lines of code
11,161
Activity Months2
Your Network
23 people
Work History
June 2025
5 Commits • 1 Features
Jun 1, 2025June 2025: Delivered a major upgrade to the Powerlifting module's nonlinear regression workflow, enabling more accurate age vs. deadlift growth-decay modeling and stronger decision support for training programs. Key elements include updated dataset references, enhanced growth-decay curve visualization and fitting, a calculus-based derivation with bootstrap confidence intervals for peak deadlift age, and refreshed instructional worksheets and solution HTML. These improvements increase modelling accuracy, clarity, and reproducibility, driving better user outcomes and trust in analytics.
5 Commits • 1 Features
Jun 1, 2025June 2025: Delivered a major upgrade to the Powerlifting module's nonlinear regression workflow, enabling more accurate age vs. deadlift growth-decay modeling and stronger decision support for training programs. Key elements include updated dataset references, enhanced growth-decay curve visualization and fitting, a calculus-based derivation with bootstrap confidence intervals for peak deadlift age, and refreshed instructional worksheets and solution HTML. These improvements increase modelling accuracy, clarity, and reproducibility, driving better user outcomes and trust in analytics.
June 2025
May 2025
1 Commits • 1 Features
May 1, 2025May 2025: Focused on repository hygiene and alignment of reviewer workflows within iramler/slu_score_module_development. Completed documentation cleanup by removing obsolete SCORE_Student_Reviewer_Form.docx. No code changes or feature additions were required, preserving system stability while simplifying future maintenance and audits.
May 2025
1 Commits • 1 Features
May 1, 2025May 2025: Focused on repository hygiene and alignment of reviewer workflows within iramler/slu_score_module_development. Completed documentation cleanup by removing obsolete SCORE_Student_Reviewer_Form.docx. No code changes or feature additions were required, preserving system stability while simplifying future maintenance and audits.
Activity
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Quality Metrics
Correctness83.4%
Maintainability83.4%
Architecture83.4%
Performance76.6%
AI Usage26.6%
Skills & Technologies
Programming Languages
HTMLMarkdownR
Technical Skills
CalculusData AnalysisData VisualizationFront End DevelopmentNon-linear RegressionR ProgrammingRegression ModelingStatistical Modeling
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