Comprehensive Data Science Workflow in R with Academic Data

Comprehensive Data Science Workflow in R with Academic DataComprehensive Data Science Workflow in R with Academic Data

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Beiqianyi Li

• 19h

Conducted a complete data science workflow in R using real-world academic data from 53 Pennsylvania schools. Merged and cleaned four heterogeneous datasets, performed descriptive statistical analysis, and built three incremental regression models to identify key predictors of student academic outcomes. Synthesized findings into a professional R Markdown report with interactive visualizations built using plotly.

Data Visualization Data Analysis Research R

Aisha Kiran

• Apr 29

Analyzed Superstore dataset to uncover sales trends, top categories, and regional performance using Google Sheets.

Tools Used: Google Sheets (formulas, pivot tables, charts)

Key Insights:

· Identified top-selling product categories and sub-categories.

· Highlighted regions with highest sales and revenue patterns.

· Visualized trends to support business decisions.

Data Visualization Data Analysis SQL Google Sheets

Ritvik Tiwari

• Apr 29

:Designed and developed a responsive school website with a clean UI and smooth user experience using HTML & CSS.

Web Development Website CSS HTML5 Python Visual Studio Code

Muyideenaliyah Ayomide

• Apr 30

nice

Bryan Munuve

• Apr 28

Built an interactive Streamlit dashboard that models revenue recovery scenarios for e-commerce stores. Allows filtering by customer state, product category, and payment type. Three interactive sliders model recovery assumptions — late delivery reduction, customer churn rate, and cancellation recovery rate — and instantly recalculate dollar outcomes. Identified $333,874 in structural revenue risk across 99,441 orders with recovery potential of $40K–$137K depending on execution.