https://github.com/ankitsharma-tech/student-success-analysis
Student success analysis – statisitical data analyisis AI project
https://github.com/ankitsharma-tech/student-success-analysis
ai artificial-intelligence r statistical-analysis statistical-data-analysis statistics
Last synced: 8 months ago
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Student success analysis – statisitical data analyisis AI project
- Host: GitHub
- URL: https://github.com/ankitsharma-tech/student-success-analysis
- Owner: ankitsharma-tech
- License: mit
- Created: 2025-09-18T17:49:39.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2025-09-18T17:53:18.000Z (9 months ago)
- Last Synced: 2025-09-18T20:19:47.424Z (9 months ago)
- Topics: ai, artificial-intelligence, r, statistical-analysis, statistical-data-analysis, statistics
- Language: HTML
- Homepage:
- Size: 11.5 MB
- Stars: 15
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Audit: auditorne/1-auditorna-vjezba/.DS_Store
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README
# 🎓 Student Success Analysis
## Final report: [report.pdf](./report.pdf)
## 📖 Project Overview
The main goal of this project was to create a comprehensive report explaining concepts of **statistical data analysis** applied to an existing dataset.
- The choice of statistical methods was flexible, as long as they were relevant and covered in the course curriculum.
- The report included test cases, either from the recommended list provided by faculty or created by team members.
- **R language** was used for data analysis and report generation.
Project evaluation was based on:
1. **Report quality**
2. **Oral examination** testing knowledge of theoretical concepts (e.g., when to use a test, test assumptions, and method details).
---
## 📊 Dataset
The dataset consists of survey responses and student grades in **mathematics** and **Portuguese** from two high schools.
Collecting this type of data is essential for analyzing and improving the quality of the education system.
More details: [pdfs/dataset_documentation.pdf](./pdfs/dataset_documentation.pdf)
---
## 📂 Directory Structure
| Directory | Description |
| ----------------------------- | -------------------------------------------------- |
| [auditorne](./auditorne/) | Reference to existing problems and their solutions |
| [cheatsheets](./cheatsheets/) | Tidyverse cheat sheets in PDF format |
| [pdfs](./pdfs/) | Dataset and project descriptions |
| [src](./src/) | R Markdown source files and dataset |
---
## ⚙️ Installation
### Windows
- Install [RStudio](https://www.rstudio.com/products/rstudio/download/#download)
- Install [R](https://cran.r-project.org/bin/windows/base/)
### Linux
- Install [RStudio](https://www.rstudio.com/products/rstudio/download/#download)
- Install R and tidyverse dependencies:
```bash
sudo apt-get install r-cran-curl r-cran-openssl r-cran-xml2 libxml2-dev
```
## 📦 R Packages Setup
1. Open **RStudio** → Open Project → `student-success-analysis.Rproj`
2. The file `student-success-analysis.Rmd` should open automatically
- If not, navigate to it in the **Files** panel and double-click
3. Run the first code chunk (`Ctrl + Shift + Enter`) containing the `library` functions
4. A popup will prompt to install required packages → click **Yes**
5. Installation may take ~20 minutes
---
## 📝 Notes
**KS Test:**
- If _p = 1_ → data surely come from the same distribution
- If _p = 0_ → data come from different distributions
## 📋 To-Do
- [ ] Spellcheck the report
- [x] Write introduction to the problem