This repository contains all coursework, reports, and source codes from the Data Analysis and Statistical Modeling course at Guangzhou International Campus (GZIC), South China University of Technology.
The repository includes:
-
Final Project
- Complete project report (PDF)
- Presentation slides (PPTX)
- R Markdown source files and HTML/PDF outputs
-
Lab 1–7
- Each lab folder contains the
.Rmd,.html, and.pdfversions of lab reports. - Topics include:
- Data Introduction
- Probability & Simulations
- Normal Distribution
- Statistical Inference
- Linear Regression
- Data Modeling & Prediction
- Each lab folder contains the
-
Datasets
Admission_Predict.csvandAdmission_Predict_Ver1.1.csv
— used in my Final Project titled Graduate Admissions: Predictive Modeling and Statistical Analysis.
The course focuses on data-driven reasoning, statistical modeling, and inference using R.
Students learn to explore, visualize, and model data through practical labs and a final analytical project.
Key skills covered:
- Descriptive & Inferential Statistics
- Simulation & Probability Analysis
- Hypothesis Testing
- Regression Modeling
- R Markdown for Reproducible Reports
- Language: R (RStudio)
- Report Format: R Markdown → HTML/PDF
- Visualization: ggplot2, base R graphics
- Data: CSV-based datasets for modeling and simulation
Chen Sihan (陈思涵)
Data Analysis & Modeling @ GZIC, SCUT
📧 Contact: 202330420212@mail.scut.edu.cn
⚠️ This repository is for academic sharing and learning purposes only. Please do not copy directly for submission.