t-kist/Bayesian-Statistics-for-Astrophysics-2024
Nov 2024 – Dec 2024
2 Months active
Languages Used
JSONJupyter NotebookPythonMarkdown
Technical Skills
Academic WritingBayesian InferenceData AnalysisJupyter NotebookMatplotlibNumPy
YannickJong
PROFILE
Yannickjong
Contributed to the Bayesian-Statistics-for-Astrophysics-2024 repository by developing and refining educational materials focused on parameter estimation and hypothesis testing in astrophysics. Enhanced Jupyter Notebooks with improved bootstrap sampling, curve fitting workflows, and foundational statistical concepts, using Python, NumPy, and Matplotlib to support robust data analysis. Addressed notebook execution metadata to ensure accurate reproducibility and streamlined iteration. Upgraded lecture materials with clearer definitions, practical examples, and improved navigation, while also refining plotting aesthetics, grammar, and equation formatting. This work strengthened the clarity, usability, and reliability of course content, supporting both instructional delivery and future reuse in academic settings.
Overall Statistics
Feature vs Bugs
75%Features
Repository Contributions
12Total
Bugs
1
Commits
12
Features
3
Lines of code
1,186
Activity Months2
Your Network
27 peopleShared Repositories
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[MaraWB]Member
[nielsklerk]Member
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EmmaVolkersMember
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RevennaMember
Work History
December 2024
9 Commits • 2 Features
Dec 1, 2024December 2024 performance summary for t-kist/Bayesian-Statistics-for-Astrophysics-2024. Delivered two major feature sets—Hypothesis Testing Education Enhancements and Lecture Materials/Notebook Upgrades—along with targeted editorial and navigation improvements to improve readability, usability, and maintainability. These changes enhance instructional clarity, learner engagement, and reusability of course materials for future semesters.
9 Commits • 2 Features
Dec 1, 2024December 2024 performance summary for t-kist/Bayesian-Statistics-for-Astrophysics-2024. Delivered two major feature sets—Hypothesis Testing Education Enhancements and Lecture Materials/Notebook Upgrades—along with targeted editorial and navigation improvements to improve readability, usability, and maintainability. These changes enhance instructional clarity, learner engagement, and reusability of course materials for future semesters.
December 2024
November 2024
3 Commits • 1 Features
Nov 1, 2024In November 2024, the Bayesian-Statistics-for-Astrophysics-2024 repository advanced the parameter estimation workflow and reinforced notebook reliability through focused feature work and stability fixes. A refined tutorial notebook now uses improved bootstrap sampling and a curve_fit-based fitting workflow to estimate true parameters, and introduces foundational hypothesis testing concepts (null/alternative hypotheses, p-values) to guide analysis. A notebook execution metadata fix was implemented to accurately reflect re-execution, including updated timestamps/counts and cell status, addressing previous inconsistencies. These changes collectively enhance analytical reliability, shorten iteration cycles, and provide clearer statistical guidance for users.
November 2024
3 Commits • 1 Features
Nov 1, 2024In November 2024, the Bayesian-Statistics-for-Astrophysics-2024 repository advanced the parameter estimation workflow and reinforced notebook reliability through focused feature work and stability fixes. A refined tutorial notebook now uses improved bootstrap sampling and a curve_fit-based fitting workflow to estimate true parameters, and introduces foundational hypothesis testing concepts (null/alternative hypotheses, p-values) to guide analysis. A notebook execution metadata fix was implemented to accurately reflect re-execution, including updated timestamps/counts and cell status, addressing previous inconsistencies. These changes collectively enhance analytical reliability, shorten iteration cycles, and provide clearer statistical guidance for users.
Activity
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Quality Metrics
Correctness92.4%
Maintainability91.6%
Architecture88.4%
Performance88.2%
AI Usage20.0%
Skills & Technologies
Programming Languages
JSONJupyter NotebookMarkdownPython
Technical Skills
Academic ResearchAcademic WritingAstrophysicsBayesian InferenceData AnalysisData ScienceData VisualizationDocumentationHypothesis TestingJupyter NotebookJupyter NotebooksMachine LearningMatplotlibNumPyPython
Repositories Contributed To
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